{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/mirkoheinzel/Documents/Publications/IMF/IMF_survey/1_replication/Heinzel_Metinosy_Kern_Reinsberg_ISQ24/Heinzel_Metinosy_Kern_Reinsberg_ISQ24_log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 3 Dec 2024, 11:38:24

{com}. do "/var/folders/yy/hvkr_fn55z919545kdqvjwxr0000gn/T//SD01116.000000"
{txt}
{com}. use "IMFMonitor_Conditions_Main.dta", clear
{txt}
{com}. collapse (sum) BA1DEB BA1ENV BA1EXT BA1FIN BA1FP BA1INS BA1LAB BA1OTH BA1POV BA1PRI BA1RTP BA1SOE BA1SP BA1TOT, by(year)
{txt}
{com}. 
. gen share_env= BA1ENV/BA1TOT
{txt}
{com}. gen share_ins= BA1INS/BA1TOT
{txt}
{com}. gen share_pov= BA1POV/BA1TOT
{txt}
{com}. gen share_soc= BA1SP/BA1TOT
{txt}
{com}. 
. gen perc_env=share_env*100
{txt}
{com}. gen perc_ins=share_ins*100
{txt}
{com}. gen perc_pov=share_pov*100
{txt}
{com}. gen perc_soc=share_soc*100
{txt}
{com}. 
. graph bar perc_pov perc_ins perc_soc perc_env, over(year) scheme(plotplainblind) stack ylabel(0(1)15)
{res}{txt}
{com}. 
. *Figure 2: support for IMF programs
. use  "IMF_survey_experiment.dta", clear
{txt}(File created by user 'sujoy.das' at Wed Jun  7 18:44:55 2023)

{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}     17.24
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0451
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0433
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0284
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5282

{txt}{ralign 78:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2303392{col 26}{space 2} .0443747{col 37}{space 1}   -5.19{col 46}{space 3}0.000{col 54}{space 4}-.3173519{col 67}{space 3}-.1433266
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0589854{col 26}{space 2} .0437678{col 37}{space 1}   -1.35{col 46}{space 3}0.178{col 54}{space 4} -.144808{col 67}{space 3} .0268371
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1664032{col 26}{space 2} .0436616{col 37}{space 1}   -3.81{col 46}{space 3}0.000{col 54}{space 4}-.2520175{col 67}{space 3}-.0807888
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0399676{col 26}{space 2} .0446187{col 37}{space 1}    0.90{col 46}{space 3}0.370{col 54}{space 4}-.0475234{col 67}{space 3} .1274586
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3411422{col 26}{space 2} .0453112{col 37}{space 1}   -7.53{col 46}{space 3}0.000{col 54}{space 4}-.4299913{col 67}{space 3}-.2522931
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1674544{col 26}{space 2} .0444102{col 37}{space 1}   -3.77{col 46}{space 3}0.000{col 54}{space 4}-.2545368{col 67}{space 3} -.080372
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1545761{col 26}{space 2} .0438521{col 37}{space 1}   -3.52{col 46}{space 3}0.000{col 54}{space 4} -.240564{col 67}{space 3}-.0685882
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1295466{col 26}{space 2} .0434812{col 37}{space 1}   -2.98{col 46}{space 3}0.003{col 54}{space 4}-.2148073{col 67}{space 3}-.0442859
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.083112{col 26}{space 2} .0665442{col 37}{space 1}   61.36{col 46}{space 3}0.000{col 54}{space 4} 3.952627{col 67}{space 3} 4.213596
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ  , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     5,286
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5036795 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4963205 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4969065 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5030935 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5123948 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4876052 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5028972 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4971028 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5170588 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4829412 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5067507 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4932493 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4864326 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5135674 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5030232 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4969768 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.60105{col 26}{space 2} .0335753{col 37}{space 1}  107.25{col 46}{space 3}0.000{col 54}{space 4} 3.535244{col 67}{space 3} 3.666856
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.370711{col 26}{space 2} .0304978{col 37}{space 1}  110.52{col 46}{space 3}0.000{col 54}{space 4} 3.310936{col 67}{space 3} 3.430485
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.516403{col 26}{space 2} .0322318{col 37}{space 1}  109.10{col 46}{space 3}0.000{col 54}{space 4}  3.45323{col 67}{space 3} 3.579576
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.457418{col 26}{space 2} .0315202{col 37}{space 1}  109.69{col 46}{space 3}0.000{col 54}{space 4} 3.395639{col 67}{space 3} 3.519196
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.567867{col 26}{space 2} .0321349{col 37}{space 1}  111.03{col 46}{space 3}0.000{col 54}{space 4} 3.504884{col 67}{space 3}  3.63085
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.401464{col 26}{space 2} .0315169{col 37}{space 1}  107.92{col 46}{space 3}0.000{col 54}{space 4} 3.339692{col 67}{space 3} 3.463236
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.65148{col 26}{space 2} .0312753{col 37}{space 1}  116.75{col 46}{space 3}0.000{col 54}{space 4} 3.590181{col 67}{space 3} 3.712778
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.310337{col 26}{space 2} .0335655{col 37}{space 1}   98.62{col 46}{space 3}0.000{col 54}{space 4}  3.24455{col 67}{space 3} 3.376125
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.569325{col 26}{space 2} .0324541{col 37}{space 1}  109.98{col 46}{space 3}0.000{col 54}{space 4} 3.505716{col 67}{space 3} 3.632934
{txt}{space 9}No  {c |}{col 14}{res}{space 2}  3.40187{col 26}{space 2} .0317241{col 37}{space 1}  107.23{col 46}{space 3}0.000{col 54}{space 4} 3.339692{col 67}{space 3} 3.464048
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.46686{col 26}{space 2} .0317889{col 37}{space 1}  109.06{col 46}{space 3}0.000{col 54}{space 4} 3.404555{col 67}{space 3} 3.529165
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.506828{col 26}{space 2} .0325499{col 37}{space 1}  107.74{col 46}{space 3}0.000{col 54}{space 4} 3.443031{col 67}{space 3} 3.570624
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.566113{col 26}{space 2} .0313827{col 37}{space 1}  113.63{col 46}{space 3}0.000{col 54}{space 4} 3.504604{col 67}{space 3} 3.627622
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.411537{col 26}{space 2} .0323814{col 37}{space 1}  105.35{col 46}{space 3}0.000{col 54}{space 4} 3.348071{col 67}{space 3} 3.475004
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.55111{col 26}{space 2} .0316167{col 37}{space 1}  112.32{col 46}{space 3}0.000{col 54}{space 4} 3.489142{col 67}{space 3} 3.613077
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.421563{col 26}{space 2} .0319397{col 37}{space 1}  107.13{col 46}{space 3}0.000{col 54}{space 4} 3.358962{col 67}{space 3} 3.484164
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support
{txt}
{com}. 
. coefplot support  , xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. *Figure 3: pay taxes and spending cuts
. reghdfe taxes i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}      7.48
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0281
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0262
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0126
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5697

{txt}{ralign 78:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}       taxes{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.155126{col 26}{space 2} .0451633{col 37}{space 1}   -3.43{col 46}{space 3}0.001{col 54}{space 4} -.243685{col 67}{space 3} -.066567
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0302376{col 26}{space 2} .0466195{col 37}{space 1}   -0.65{col 46}{space 3}0.517{col 54}{space 4} -.121652{col 67}{space 3} .0611769
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1646791{col 26}{space 2} .0457554{col 37}{space 1}   -3.60{col 46}{space 3}0.000{col 54}{space 4}-.2543992{col 67}{space 3}-.0749589
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0108343{col 26}{space 2} .0448956{col 37}{space 1}    0.24{col 46}{space 3}0.809{col 54}{space 4}-.0771998{col 67}{space 3} .0988684
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2209302{col 26}{space 2} .0463686{col 37}{space 1}   -4.76{col 46}{space 3}0.000{col 54}{space 4}-.3118526{col 67}{space 3}-.1300077
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1015567{col 26}{space 2} .0461412{col 37}{space 1}   -2.20{col 46}{space 3}0.028{col 54}{space 4}-.1920332{col 67}{space 3}-.0110802
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0505237{col 26}{space 2} .0456419{col 37}{space 1}   -1.11{col 46}{space 3}0.268{col 54}{space 4}-.1400211{col 67}{space 3} .0389737
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.105819{col 26}{space 2} .0456416{col 37}{space 1}   -2.32{col 46}{space 3}0.020{col 54}{space 4}-.1953158{col 67}{space 3}-.0163222
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.761466{col 26}{space 2} .0721881{col 37}{space 1}   52.11{col 46}{space 3}0.000{col 54}{space 4} 3.619915{col 67}{space 3} 3.903017
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     5,286
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5036795 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4963205 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4969065 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5030935 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5123948 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4876052 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5028972 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4971028 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5170588 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4829412 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5067507 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4932493 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4864326 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5135674 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5030232 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4969768 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.436015{col 26}{space 2} .0341979{col 37}{space 1}  100.47{col 46}{space 3}0.000{col 54}{space 4} 3.368988{col 67}{space 3} 3.503042
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.280889{col 26}{space 2} .0330044{col 37}{space 1}   99.41{col 46}{space 3}0.000{col 54}{space 4} 3.216201{col 67}{space 3} 3.345576
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.374235{col 26}{space 2} .0352996{col 37}{space 1}   95.59{col 46}{space 3}0.000{col 54}{space 4} 3.305049{col 67}{space 3} 3.443421
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.343997{col 26}{space 2} .0328813{col 37}{space 1}  101.70{col 46}{space 3}0.000{col 54}{space 4} 3.279551{col 67}{space 3} 3.408444
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.439321{col 26}{space 2} .0349142{col 37}{space 1}   98.51{col 46}{space 3}0.000{col 54}{space 4}  3.37089{col 67}{space 3} 3.507752
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.274642{col 26}{space 2} .0326012{col 37}{space 1}  100.45{col 46}{space 3}0.000{col 54}{space 4} 3.210745{col 67}{space 3} 3.338539
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.465719{col 26}{space 2} .0332423{col 37}{space 1}  104.26{col 46}{space 3}0.000{col 54}{space 4} 3.400565{col 67}{space 3} 3.530873
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.244789{col 26}{space 2} .0348129{col 37}{space 1}   93.21{col 46}{space 3}0.000{col 54}{space 4} 3.176557{col 67}{space 3} 3.313021
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.409115{col 26}{space 2} .0340651{col 37}{space 1}  100.08{col 46}{space 3}0.000{col 54}{space 4} 3.342349{col 67}{space 3} 3.475882
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.307559{col 26}{space 2} .0338115{col 37}{space 1}   97.82{col 46}{space 3}0.000{col 54}{space 4} 3.241289{col 67}{space 3} 3.373828
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.353637{col 26}{space 2} .0341517{col 37}{space 1}   98.20{col 46}{space 3}0.000{col 54}{space 4} 3.286701{col 67}{space 3} 3.420573
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.364471{col 26}{space 2} .0328711{col 37}{space 1}  102.35{col 46}{space 3}0.000{col 54}{space 4} 3.300045{col 67}{space 3} 3.428897
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.38497{col 26}{space 2} .0339712{col 37}{space 1}   99.64{col 46}{space 3}0.000{col 54}{space 4} 3.318388{col 67}{space 3} 3.451552
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.334446{col 26}{space 2} .0335721{col 37}{space 1}   99.32{col 46}{space 3}0.000{col 54}{space 4} 3.268646{col 67}{space 3} 3.400246
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.411612{col 26}{space 2} .0339494{col 37}{space 1}  100.49{col 46}{space 3}0.000{col 54}{space 4} 3.345073{col 67}{space 3} 3.478152
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.305793{col 26}{space 2} .0335917{col 37}{space 1}   98.41{col 46}{space 3}0.000{col 54}{space 4} 3.239955{col 67}{space 3} 3.371632
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo taxes
{txt}
{com}. 
. reghdfe cuts i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}     10.38
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0351
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0333
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0187
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5863

{txt}{ralign 78:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        cuts{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1192542{col 26}{space 2} .0450769{col 37}{space 1}   -2.65{col 46}{space 3}0.008{col 54}{space 4}-.2076438{col 67}{space 3}-.0308647
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0682027{col 26}{space 2} .0459075{col 37}{space 1}   -1.49{col 46}{space 3}0.137{col 54}{space 4}-.1582209{col 67}{space 3} .0218156
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2006735{col 26}{space 2} .0456124{col 37}{space 1}   -4.40{col 46}{space 3}0.000{col 54}{space 4}-.2901132{col 67}{space 3}-.1112339
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0389614{col 26}{space 2} .0459258{col 37}{space 1}   -0.85{col 46}{space 3}0.396{col 54}{space 4}-.1290155{col 67}{space 3} .0510928
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.241846{col 26}{space 2} .0477513{col 37}{space 1}   -5.06{col 46}{space 3}0.000{col 54}{space 4}-.3354798{col 67}{space 3}-.1482123
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}  -.18123{col 26}{space 2} .0454209{col 37}{space 1}   -3.99{col 46}{space 3}0.000{col 54}{space 4}-.2702941{col 67}{space 3}-.0921659
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1119305{col 26}{space 2} .0459902{col 37}{space 1}   -2.43{col 46}{space 3}0.015{col 54}{space 4}-.2021109{col 67}{space 3}  -.02175
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1645639{col 26}{space 2} .0460117{col 37}{space 1}   -3.58{col 46}{space 3}0.000{col 54}{space 4}-.2547866{col 67}{space 3}-.0743413
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.198066{col 26}{space 2} .0720766{col 37}{space 1}   58.24{col 46}{space 3}0.000{col 54}{space 4} 4.056734{col 67}{space 3} 4.339398
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     5,286
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5036795 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4963205 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4969065 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5030935 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5123948 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4876052 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5028972 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4971028 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5170588 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4829412 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5067507 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4932493 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4864326 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5135674 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5030232 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4969768 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.701079{col 26}{space 2} .0348651{col 37}{space 1}  106.15{col 46}{space 3}0.000{col 54}{space 4} 3.632745{col 67}{space 3} 3.769414
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.581825{col 26}{space 2} .0332776{col 37}{space 1}  107.63{col 46}{space 3}0.000{col 54}{space 4} 3.516602{col 67}{space 3} 3.647048
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.676203{col 26}{space 2} .0350828{col 37}{space 1}  104.79{col 46}{space 3}0.000{col 54}{space 4} 3.607442{col 67}{space 3} 3.744964
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.608001{col 26}{space 2}  .033636{col 37}{space 1}  107.27{col 46}{space 3}0.000{col 54}{space 4} 3.542075{col 67}{space 3} 3.673926
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.73974{col 26}{space 2} .0346063{col 37}{space 1}  108.07{col 46}{space 3}0.000{col 54}{space 4} 3.671913{col 67}{space 3} 3.807568
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.539067{col 26}{space 2} .0338919{col 37}{space 1}  104.42{col 46}{space 3}0.000{col 54}{space 4}  3.47264{col 67}{space 3} 3.605494
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.758688{col 26}{space 2} .0339188{col 37}{space 1}  110.81{col 46}{space 3}0.000{col 54}{space 4} 3.692209{col 67}{space 3} 3.825168
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.516842{col 26}{space 2} .0360734{col 37}{space 1}   97.49{col 46}{space 3}0.000{col 54}{space 4}  3.44614{col 67}{space 3} 3.587545
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.731283{col 26}{space 2} .0339176{col 37}{space 1}  110.01{col 46}{space 3}0.000{col 54}{space 4} 3.664805{col 67}{space 3}  3.79776
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.550053{col 26}{space 2} .0344866{col 37}{space 1}  102.94{col 46}{space 3}0.000{col 54}{space 4}  3.48246{col 67}{space 3} 3.617645
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.661259{col 26}{space 2} .0341552{col 37}{space 1}  107.19{col 46}{space 3}0.000{col 54}{space 4} 3.594316{col 67}{space 3} 3.728202
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.622297{col 26}{space 2} .0345833{col 37}{space 1}  104.74{col 46}{space 3}0.000{col 54}{space 4} 3.554515{col 67}{space 3}  3.69008
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.699375{col 26}{space 2} .0346127{col 37}{space 1}  106.88{col 46}{space 3}0.000{col 54}{space 4} 3.631535{col 67}{space 3} 3.767215
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.587444{col 26}{space 2} .0341675{col 37}{space 1}  105.00{col 46}{space 3}0.000{col 54}{space 4} 3.520477{col 67}{space 3} 3.654411
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.723675{col 26}{space 2} .0345892{col 37}{space 1}  107.65{col 46}{space 3}0.000{col 54}{space 4} 3.655882{col 67}{space 3} 3.791469
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.559112{col 26}{space 2} .0342021{col 37}{space 1}  104.06{col 46}{space 3}0.000{col 54}{space 4} 3.492077{col 67}{space 3} 3.626146
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo cuts
{txt}
{com}. 
. coefplot taxes cuts  , xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. *Figure 4: simulation
. 
. foreach x of varlist invest tariff debt corrupt poverty privatize climate genderequ{c -(}
{txt}  2{com}. gen zero_`x'=`x' 
{txt}  3{com}. replace zero_`x'=0 if zero_`x'==2
{txt}  4{com}. {c )-}
{txt}(2,636 real changes made)
(2,670 real changes made)
(2,600 real changes made)
(2,543 real changes made)
(2,615 real changes made)
(2,629 real changes made)
(2,708 real changes made)
(2,634 real changes made)

{com}. 
. reghdfe support zero_invest zero_tariff zero_debt zero_corrupt zero_poverty zero_privatize zero_climate zero_genderequ [pw = weight] , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}     17.24
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0451
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0433
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0284
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5282

{txt}{ralign 80:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}       support{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}zero_invest {c |}{col 16}{res}{space 2} .2303392{col 28}{space 2} .0443747{col 39}{space 1}    5.19{col 48}{space 3}0.000{col 56}{space 4} .1433266{col 69}{space 3} .3173519
{txt}{space 3}zero_tariff {c |}{col 16}{res}{space 2} .0589854{col 28}{space 2} .0437678{col 39}{space 1}    1.35{col 48}{space 3}0.178{col 56}{space 4}-.0268371{col 69}{space 3}  .144808
{txt}{space 5}zero_debt {c |}{col 16}{res}{space 2} .1664032{col 28}{space 2} .0436616{col 39}{space 1}    3.81{col 48}{space 3}0.000{col 56}{space 4} .0807888{col 69}{space 3} .2520175
{txt}{space 2}zero_corrupt {c |}{col 16}{res}{space 2} .3411422{col 28}{space 2} .0453112{col 39}{space 1}    7.53{col 48}{space 3}0.000{col 56}{space 4} .2522931{col 69}{space 3} .4299913
{txt}{space 2}zero_poverty {c |}{col 16}{res}{space 2} .1674544{col 28}{space 2} .0444102{col 39}{space 1}    3.77{col 48}{space 3}0.000{col 56}{space 4}  .080372{col 69}{space 3} .2545368
{txt}zero_privatize {c |}{col 16}{res}{space 2}-.0399676{col 28}{space 2} .0446187{col 39}{space 1}   -0.90{col 48}{space 3}0.370{col 56}{space 4}-.1274586{col 69}{space 3} .0475234
{txt}{space 2}zero_climate {c |}{col 16}{res}{space 2} .1545761{col 28}{space 2} .0438521{col 39}{space 1}    3.52{col 48}{space 3}0.000{col 56}{space 4} .0685882{col 69}{space 3}  .240564
{txt}zero_genderequ {c |}{col 16}{res}{space 2} .1295466{col 28}{space 2} .0434812{col 39}{space 1}    2.98{col 48}{space 3}0.003{col 56}{space 4} .0442859{col 69}{space 3} .2148073
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 2.874632{col 28}{space 2} .0660967{col 39}{space 1}   43.49{col 48}{space 3}0.000{col 56}{space 4} 2.745025{col 69}{space 3} 3.004239
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. 
. predict yhat
{txt}(option xb assumed; fitted values)

{com}. predict se, stdp
{txt}
{com}. gen lb = yhat - 1.96*se
{txt}
{com}. gen ub = yhat + 1.96*se
{txt}
{com}. 
. *display values
. *WC
. sum yhat if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==0 & zero_poverty==0 & zero_climate==0 & zero_genderequ==0

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}yhat {c |}{res}         18    3.290392           0   3.290392   3.290392
{txt}
{com}. sum lb if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==0 & zero_poverty==0 & zero_climate==0 & zero_genderequ==0

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 10}lb {c |}{res}         18    3.155816           0   3.155816   3.155816
{txt}
{com}. sum ub if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==0 & zero_poverty==0 & zero_climate==0 & zero_genderequ==0

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 10}ub {c |}{res}         18    3.424968           0   3.424968   3.424968
{txt}
{com}. 
. *yhat 3.290392
. *lb 3.155816
. *up 3.424968
. 
. *PWC
. *WC
. sum yhat if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==1 & zero_poverty==0 & zero_climate==0 & zero_genderequ==0

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}yhat {c |}{res}         24    3.631534    4.54e-16   3.631534   3.631534
{txt}
{com}. sum lb if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==1 & zero_poverty==0 & zero_climate==0 & zero_genderequ==0

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 10}lb {c |}{res}         24    3.500903           0   3.500903   3.500903
{txt}
{com}. sum ub if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==1 & zero_poverty==0 & zero_climate==0 & zero_genderequ==0

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 10}ub {c |}{res}         24    3.762166           0   3.762166   3.762166
{txt}
{com}. 
. *yhat 3.631534
. *lb 3.500903
. *up 3.762166
. 
. *GRID
. *WC
. sum yhat if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==1 & zero_poverty==1 & zero_climate==1 & zero_genderequ==1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}yhat {c |}{res}         20    4.083112           0   4.083112   4.083112
{txt}
{com}. sum lb if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==1 & zero_poverty==1 & zero_climate==1 & zero_genderequ==1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 10}lb {c |}{res}         20    3.952685           0   3.952685   3.952685
{txt}
{com}. sum ub if zero_invest==1 & zero_tariff==1 & zero_debt==1 & zero_privatize==1 & zero_corrupt==1 & zero_poverty==1 & zero_climate==1 & zero_genderequ==1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 10}ub {c |}{res}         20    4.213538           0   4.213538   4.213538
{txt}
{com}. 
. *yhat 4.083112
. *lb 3.952685
. *up 4.213538
. 
. *create plot
. clear all 
{res}{txt}
{com}. matrix C = J(3,3,.)
{txt}
{com}. 
. matrix input C = (3.290392,3.155816, 3.424968 \ 3.631534,3.500903,3.762166 \4.083112, 3.952685, 4.213538)
{txt}
{com}. 
. matrix colnames C = estimate ll95 ul95
{txt}
{com}. matrix rownames C = WC PWC GRID
{txt}
{com}. matrix list C
{res}
{txt}C[3,3]
      estimate      ll95      ul95
  WC {res} 3.290392  3.155816  3.424968
{txt} PWC {res} 3.631534  3.500903  3.762166
{txt}GRID {res} 4.083112  3.952685  4.213538
{reset}
{com}. coefplot matrix(C[,1]), ci((C[,2] C[,3])) scheme(plotplainblind) xlabel(3(0.5)4.5)
{res}{txt}
{com}. 
. *Figure 5: by ideology
. use  "IMF_survey_experiment.dta", clear
{txt}(File created by user 'sujoy.das' at Wed Jun  7 18:44:55 2023)

{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] if q4==1 | q4==2 , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     1,100
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}    549{txt}){col 67}= {res}      2.03
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0416
{txt}{col 51}R-squared{col 67}= {res}    0.0485
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0397
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0162
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}       550{txt}{col 51}Root MSE{col 67}= {res}    1.6213

{txt}{ralign 78:(Std. Err. adjusted for {res:550} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1487729{col 26}{space 2} .1016496{col 37}{space 1}   -1.46{col 46}{space 3}0.144{col 54}{space 4}-.3484426{col 67}{space 3} .0508967
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0784368{col 26}{space 2} .1065022{col 37}{space 1}   -0.74{col 46}{space 3}0.462{col 54}{space 4}-.2876385{col 67}{space 3} .1307648
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1332455{col 26}{space 2} .1011585{col 37}{space 1}   -1.32{col 46}{space 3}0.188{col 54}{space 4}-.3319505{col 67}{space 3} .0654596
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0659808{col 26}{space 2} .0992428{col 37}{space 1}    0.66{col 46}{space 3}0.506{col 54}{space 4}-.1289612{col 67}{space 3} .2609229
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3117248{col 26}{space 2} .1035271{col 37}{space 1}   -3.01{col 46}{space 3}0.003{col 54}{space 4}-.5150825{col 67}{space 3}-.1083672
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1229677{col 26}{space 2} .1003785{col 37}{space 1}   -1.23{col 46}{space 3}0.221{col 54}{space 4}-.3201407{col 67}{space 3} .0742052
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1182486{col 26}{space 2} .1068007{col 37}{space 1}   -1.11{col 46}{space 3}0.269{col 54}{space 4}-.3280367{col 67}{space 3} .0915395
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0093523{col 26}{space 2} .1006667{col 37}{space 1}   -0.09{col 46}{space 3}0.926{col 54}{space 4}-.2070913{col 67}{space 3} .1883867
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.593474{col 26}{space 2} .1517283{col 37}{space 1}   23.68{col 46}{space 3}0.000{col 54}{space 4} 3.295435{col 67}{space 3} 3.891513
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     1,100
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.4980344 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.5019656 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.5065595 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.4934405 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5041075 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4958925 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.4895478 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.5104522 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5094584 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4905416 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5158744 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4841256 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 4}.491818 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 4}.508182 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5117358 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4882642 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.245271{col 26}{space 2} .0770741{col 37}{space 1}   42.11{col 46}{space 3}0.000{col 54}{space 4} 3.094208{col 67}{space 3} 3.396333
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.096498{col 26}{space 2} .0735444{col 37}{space 1}   42.10{col 46}{space 3}0.000{col 54}{space 4} 2.952353{col 67}{space 3} 3.240642
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.209296{col 26}{space 2} .0780831{col 37}{space 1}   41.10{col 46}{space 3}0.000{col 54}{space 4} 3.056256{col 67}{space 3} 3.362336
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.130859{col 26}{space 2} .0758269{col 37}{space 1}   41.29{col 46}{space 3}0.000{col 54}{space 4} 2.982241{col 67}{space 3} 3.279477
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.236667{col 26}{space 2} .0767498{col 37}{space 1}   42.17{col 46}{space 3}0.000{col 54}{space 4}  3.08624{col 67}{space 3} 3.387094
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.103422{col 26}{space 2} .0735016{col 37}{space 1}   42.22{col 46}{space 3}0.000{col 54}{space 4} 2.959361{col 67}{space 3} 3.247482
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.323506{col 26}{space 2} .0759292{col 37}{space 1}   43.77{col 46}{space 3}0.000{col 54}{space 4} 3.174687{col 67}{space 3} 3.472324
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.011781{col 26}{space 2} .0759788{col 37}{space 1}   39.64{col 46}{space 3}0.000{col 54}{space 4} 2.862865{col 67}{space 3} 3.160696
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.230123{col 26}{space 2} .0764839{col 37}{space 1}   42.23{col 46}{space 3}0.000{col 54}{space 4} 3.080218{col 67}{space 3} 3.380029
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.107156{col 26}{space 2} .0731299{col 37}{space 1}   42.49{col 46}{space 3}0.000{col 54}{space 4} 2.963824{col 67}{space 3} 3.250488
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.136912{col 26}{space 2} .0747606{col 37}{space 1}   41.96{col 46}{space 3}0.000{col 54}{space 4} 2.990383{col 67}{space 3}  3.28344
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.202892{col 26}{space 2} .0742675{col 37}{space 1}   43.13{col 46}{space 3}0.000{col 54}{space 4} 3.057331{col 67}{space 3} 3.348454
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.230683{col 26}{space 2} .0757542{col 37}{space 1}   42.65{col 46}{space 3}0.000{col 54}{space 4} 3.082208{col 67}{space 3} 3.379159
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.112435{col 26}{space 2}  .078341{col 37}{space 1}   39.73{col 46}{space 3}0.000{col 54}{space 4} 2.958889{col 67}{space 3}  3.26598
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.175158{col 26}{space 2} .0693346{col 37}{space 1}   45.79{col 46}{space 3}0.000{col 54}{space 4} 3.039265{col 67}{space 3} 3.311051
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.165806{col 26}{space 2} .0804789{col 37}{space 1}   39.34{col 46}{space 3}0.000{col 54}{space 4}  3.00807{col 67}{space 3} 3.323542
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_lw
{txt}
{com}. 
. *centre
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] if q4==3 | q4==4 , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,350
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   1174{txt}){col 67}= {res}      7.38
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0388
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0347
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0275
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     1,175{txt}{col 51}Root MSE{col 67}= {res}    1.4325

{txt}{ralign 78:(Std. Err. adjusted for {res:1,175} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2278265{col 26}{space 2} .0625491{col 37}{space 1}   -3.64{col 46}{space 3}0.000{col 54}{space 4}-.3505471{col 67}{space 3}-.1051059
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}  -.05945{col 26}{space 2} .0619689{col 37}{space 1}   -0.96{col 46}{space 3}0.338{col 54}{space 4}-.1810321{col 67}{space 3} .0621322
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1144721{col 26}{space 2} .0611991{col 37}{space 1}   -1.87{col 46}{space 3}0.062{col 54}{space 4} -.234544{col 67}{space 3} .0055998
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0249546{col 26}{space 2} .0635893{col 37}{space 1}    0.39{col 46}{space 3}0.695{col 54}{space 4}-.0998068{col 67}{space 3} .1497159
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3154345{col 26}{space 2} .0649979{col 37}{space 1}   -4.85{col 46}{space 3}0.000{col 54}{space 4}-.4429596{col 67}{space 3}-.1879094
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1511056{col 26}{space 2} .0619161{col 37}{space 1}   -2.44{col 46}{space 3}0.015{col 54}{space 4}-.2725841{col 67}{space 3}-.0296271
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1265584{col 26}{space 2} .0612498{col 37}{space 1}   -2.07{col 46}{space 3}0.039{col 54}{space 4}-.2467297{col 67}{space 3}-.0063871
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1356428{col 26}{space 2} .0615591{col 37}{space 1}   -2.20{col 46}{space 3}0.028{col 54}{space 4}-.2564209{col 67}{space 3}-.0148647
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.114609{col 26}{space 2} .0929215{col 37}{space 1}   44.28{col 46}{space 3}0.000{col 54}{space 4} 3.932298{col 67}{space 3} 4.296919
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     2,350
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5002004 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4997996 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.5034606 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.4965394 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5103479 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4896521 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.4939979 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.5060021 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5053493 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4946507 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5042701 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4957299 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4809824 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5190176 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.4963602 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.5036398 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.676726{col 26}{space 2}  .047741{col 37}{space 1}   77.01{col 46}{space 3}0.000{col 54}{space 4} 3.583156{col 67}{space 3} 3.770297
{txt}{space 9}No  {c |}{col 14}{res}{space 2}   3.4489{col 26}{space 2} .0405669{col 37}{space 1}   85.02{col 46}{space 3}0.000{col 54}{space 4}  3.36939{col 67}{space 3}  3.52841
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.592378{col 26}{space 2} .0429961{col 37}{space 1}   83.55{col 46}{space 3}0.000{col 54}{space 4} 3.508107{col 67}{space 3} 3.676649
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.532928{col 26}{space 2} .0451839{col 37}{space 1}   78.19{col 46}{space 3}0.000{col 54}{space 4} 3.444369{col 67}{space 3} 3.621487
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.61891{col 26}{space 2} .0438878{col 37}{space 1}   82.46{col 46}{space 3}0.000{col 54}{space 4} 3.532892{col 67}{space 3} 3.704929
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.504438{col 26}{space 2}  .043754{col 37}{space 1}   80.09{col 46}{space 3}0.000{col 54}{space 4} 3.418682{col 67}{space 3} 3.590194
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.718889{col 26}{space 2} .0434176{col 37}{space 1}   85.65{col 46}{space 3}0.000{col 54}{space 4} 3.633792{col 67}{space 3} 3.803986
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.403454{col 26}{space 2}  .046897{col 37}{space 1}   72.57{col 46}{space 3}0.000{col 54}{space 4} 3.311538{col 67}{space 3} 3.495371
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.637766{col 26}{space 2} .0454481{col 37}{space 1}   80.04{col 46}{space 3}0.000{col 54}{space 4}  3.54869{col 67}{space 3} 3.726843
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.486661{col 26}{space 2} .0426374{col 37}{space 1}   81.77{col 46}{space 3}0.000{col 54}{space 4} 3.403093{col 67}{space 3} 3.570229
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.550232{col 26}{space 2} .0435449{col 37}{space 1}   81.53{col 46}{space 3}0.000{col 54}{space 4} 3.464885{col 67}{space 3} 3.635578
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.575186{col 26}{space 2} .0457377{col 37}{space 1}   78.17{col 46}{space 3}0.000{col 54}{space 4} 3.485542{col 67}{space 3}  3.66483
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.628545{col 26}{space 2} .0429331{col 37}{space 1}   84.52{col 46}{space 3}0.000{col 54}{space 4} 3.544397{col 67}{space 3} 3.712692
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.501986{col 26}{space 2} .0446435{col 37}{space 1}   78.44{col 46}{space 3}0.000{col 54}{space 4} 3.414487{col 67}{space 3} 3.589486
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.631174{col 26}{space 2}  .045651{col 37}{space 1}   79.54{col 46}{space 3}0.000{col 54}{space 4}   3.5417{col 67}{space 3} 3.720648
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.495531{col 26}{space 2} .0422112{col 37}{space 1}   82.81{col 46}{space 3}0.000{col 54}{space 4} 3.412799{col 67}{space 3} 3.578263
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_center
{txt}
{com}. 
. *right
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] if q4==5 | q4==6, absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     1,442
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}    720{txt}){col 67}= {res}      8.95
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0717
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0652
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0513
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}       721{txt}{col 51}Root MSE{col 67}= {res}    1.5798

{txt}{ralign 78:(Std. Err. adjusted for {res:721} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3274061{col 26}{space 2} .0843718{col 37}{space 1}   -3.88{col 46}{space 3}0.000{col 54}{space 4}-.4930502{col 67}{space 3}-.1617619
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1506981{col 26}{space 2} .0816466{col 37}{space 1}   -1.85{col 46}{space 3}0.065{col 54}{space 4}-.3109919{col 67}{space 3} .0095957
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.319755{col 26}{space 2}  .084044{col 37}{space 1}   -3.80{col 46}{space 3}0.000{col 54}{space 4}-.4847556{col 67}{space 3}-.1547543
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0138673{col 26}{space 2} .0899319{col 37}{space 1}   -0.15{col 46}{space 3}0.877{col 54}{space 4}-.1904273{col 67}{space 3} .1626928
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.4528909{col 26}{space 2} .0889417{col 37}{space 1}   -5.09{col 46}{space 3}0.000{col 54}{space 4} -.627507{col 67}{space 3}-.2782747
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1916749{col 26}{space 2} .0869203{col 37}{space 1}   -2.21{col 46}{space 3}0.028{col 54}{space 4}-.3623224{col 67}{space 3}-.0210273
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1753866{col 26}{space 2} .0837435{col 37}{space 1}   -2.09{col 46}{space 3}0.037{col 54}{space 4}-.3397972{col 67}{space 3} -.010976
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1839605{col 26}{space 2} .0853184{col 37}{space 1}   -2.16{col 46}{space 3}0.031{col 54}{space 4}-.3514631{col 67}{space 3}-.0164578
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.532783{col 26}{space 2} .1297529{col 37}{space 1}   34.93{col 46}{space 3}0.000{col 54}{space 4} 4.278044{col 67}{space 3} 4.787523
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     1,442
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5117216 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4882784 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4707633 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5292367 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5141411 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4858589 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5258733 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4741267 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5476675 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4523325 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5009378 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4990622 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4964313 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5035687 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5100684 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4899316 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.812135{col 26}{space 2} .0620494{col 37}{space 1}   61.44{col 46}{space 3}0.000{col 54}{space 4} 3.690521{col 67}{space 3}  3.93375
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.484729{col 26}{space 2} .0611458{col 37}{space 1}   56.99{col 46}{space 3}0.000{col 54}{space 4} 3.364886{col 67}{space 3} 3.604573
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.732025{col 26}{space 2}   .06331{col 37}{space 1}   58.95{col 46}{space 3}0.000{col 54}{space 4}  3.60794{col 67}{space 3}  3.85611
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.581327{col 26}{space 2}  .058174{col 37}{space 1}   61.56{col 46}{space 3}0.000{col 54}{space 4} 3.467308{col 67}{space 3} 3.695346
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.807626{col 26}{space 2} .0617963{col 37}{space 1}   61.62{col 46}{space 3}0.000{col 54}{space 4} 3.686507{col 67}{space 3} 3.928744
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.487871{col 26}{space 2} .0611729{col 37}{space 1}   57.02{col 46}{space 3}0.000{col 54}{space 4} 3.367974{col 67}{space 3} 3.607768
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.857127{col 26}{space 2} .0577364{col 37}{space 1}   66.81{col 46}{space 3}0.000{col 54}{space 4} 3.743966{col 67}{space 3} 3.970289
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.404237{col 26}{space 2} .0689613{col 37}{space 1}   49.36{col 46}{space 3}0.000{col 54}{space 4} 3.269075{col 67}{space 3} 3.539398
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.747928{col 26}{space 2} .0619244{col 37}{space 1}   60.52{col 46}{space 3}0.000{col 54}{space 4} 3.626558{col 67}{space 3} 3.869297
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.556253{col 26}{space 2} .0630666{col 37}{space 1}   56.39{col 46}{space 3}0.000{col 54}{space 4} 3.432645{col 67}{space 3} 3.679861
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.658845{col 26}{space 2} .0635788{col 37}{space 1}   57.55{col 46}{space 3}0.000{col 54}{space 4} 3.534233{col 67}{space 3} 3.783457
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.644978{col 26}{space 2} .0634353{col 37}{space 1}   57.46{col 46}{space 3}0.000{col 54}{space 4} 3.520647{col 67}{space 3} 3.769309
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.740589{col 26}{space 2} .0600316{col 37}{space 1}   62.31{col 46}{space 3}0.000{col 54}{space 4}  3.62293{col 67}{space 3} 3.858249
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.565203{col 26}{space 2} .0627244{col 37}{space 1}   56.84{col 46}{space 3}0.000{col 54}{space 4} 3.442265{col 67}{space 3}  3.68814
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.742398{col 26}{space 2} .0599836{col 37}{space 1}   62.39{col 46}{space 3}0.000{col 54}{space 4} 3.624833{col 67}{space 3} 3.859964
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.558438{col 26}{space 2} .0639069{col 37}{space 1}   55.68{col 46}{space 3}0.000{col 54}{space 4} 3.433182{col 67}{space 3} 3.683693
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_rw
{txt}
{com}. 
. coefplot support_lw support_center support_rw , xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. 
. *Figure 6: by gender
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] if gender_all==1 , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,060
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   1529{txt}){col 67}= {res}     10.78
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0385
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0353
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0291
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     1,530{txt}{col 51}Root MSE{col 67}= {res}    1.5762

{txt}{ralign 78:(Std. Err. adjusted for {res:1,530} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3054593{col 26}{space 2} .0594795{col 37}{space 1}   -5.14{col 46}{space 3}0.000{col 54}{space 4}-.4221292{col 67}{space 3}-.1887893
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}   .05083{col 26}{space 2}  .059537{col 37}{space 1}    0.85{col 46}{space 3}0.393{col 54}{space 4}-.0659528{col 67}{space 3} .1676129
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1316786{col 26}{space 2} .0600797{col 37}{space 1}   -2.19{col 46}{space 3}0.029{col 54}{space 4} -.249526{col 67}{space 3}-.0138312
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0126752{col 26}{space 2} .0613454{col 37}{space 1}   -0.21{col 46}{space 3}0.836{col 54}{space 4}-.1330052{col 67}{space 3} .1076548
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.375155{col 26}{space 2} .0616439{col 37}{space 1}   -6.09{col 46}{space 3}0.000{col 54}{space 4}-.4960705{col 67}{space 3}-.2542396
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1512328{col 26}{space 2} .0597677{col 37}{space 1}   -2.53{col 46}{space 3}0.011{col 54}{space 4}-.2684681{col 67}{space 3}-.0339974
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0934447{col 26}{space 2} .0587989{col 37}{space 1}   -1.59{col 46}{space 3}0.112{col 54}{space 4}-.2087797{col 67}{space 3} .0218904
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0879788{col 26}{space 2}   .05953{col 37}{space 1}   -1.48{col 46}{space 3}0.140{col 54}{space 4}-.2047479{col 67}{space 3} .0287904
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.012288{col 26}{space 2} .0916142{col 37}{space 1}   43.80{col 46}{space 3}0.000{col 54}{space 4} 3.832585{col 67}{space 3} 4.191991
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     3,060
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5085273 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4914727 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4960759 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5039241 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5039139 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4960861 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 4}.493685 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 4}.506315 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5103127 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4896873 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5040748 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4959252 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4818234 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5181766 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5108735 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4891265 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.615999{col 26}{space 2} .0461017{col 37}{space 1}   78.44{col 46}{space 3}0.000{col 54}{space 4} 3.525641{col 67}{space 3} 3.706356
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.310539{col 26}{space 2} .0411662{col 37}{space 1}   80.42{col 46}{space 3}0.000{col 54}{space 4} 3.229855{col 67}{space 3} 3.391223
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.440259{col 26}{space 2} .0444903{col 37}{space 1}   77.33{col 46}{space 3}0.000{col 54}{space 4}  3.35306{col 67}{space 3} 3.527459
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.491089{col 26}{space 2} .0430442{col 37}{space 1}   81.10{col 46}{space 3}0.000{col 54}{space 4} 3.406724{col 67}{space 3} 3.575454
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.531198{col 26}{space 2} .0448218{col 37}{space 1}   78.78{col 46}{space 3}0.000{col 54}{space 4} 3.443349{col 67}{space 3} 3.619047
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.399519{col 26}{space 2} .0430517{col 37}{space 1}   78.96{col 46}{space 3}0.000{col 54}{space 4} 3.315139{col 67}{space 3} 3.483899
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.649582{col 26}{space 2} .0428554{col 37}{space 1}   85.16{col 46}{space 3}0.000{col 54}{space 4} 3.565587{col 67}{space 3} 3.733577
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.274427{col 26}{space 2} .0461256{col 37}{space 1}   70.99{col 46}{space 3}0.000{col 54}{space 4} 3.184023{col 67}{space 3} 3.364832
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.540874{col 26}{space 2} .0453536{col 37}{space 1}   78.07{col 46}{space 3}0.000{col 54}{space 4} 3.451982{col 67}{space 3} 3.629765
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.389641{col 26}{space 2} .0422586{col 37}{space 1}   80.21{col 46}{space 3}0.000{col 54}{space 4} 3.306816{col 67}{space 3} 3.472466
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.472291{col 26}{space 2} .0439677{col 37}{space 1}   78.97{col 46}{space 3}0.000{col 54}{space 4} 3.386116{col 67}{space 3} 3.558466
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.459616{col 26}{space 2} .0447909{col 37}{space 1}   77.24{col 46}{space 3}0.000{col 54}{space 4} 3.371828{col 67}{space 3} 3.547405
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.514294{col 26}{space 2} .0431075{col 37}{space 1}   81.52{col 46}{space 3}0.000{col 54}{space 4} 3.429805{col 67}{space 3} 3.598784
{txt}{space 9}No  {c |}{col 14}{res}{space 2}  3.42085{col 26}{space 2} .0438711{col 37}{space 1}   77.97{col 46}{space 3}0.000{col 54}{space 4} 3.334864{col 67}{space 3} 3.506836
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.508906{col 26}{space 2} .0433472{col 37}{space 1}   80.95{col 46}{space 3}0.000{col 54}{space 4} 3.423947{col 67}{space 3} 3.593865
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.420928{col 26}{space 2} .0441891{col 37}{space 1}   77.42{col 46}{space 3}0.000{col 54}{space 4} 3.334319{col 67}{space 3} 3.507537
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_men
{txt}
{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] if gender_all==2 , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,226
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   1112{txt}){col 67}= {res}     10.56
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0700
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0658
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0398
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     1,113{txt}{col 51}Root MSE{col 67}= {res}    1.4444

{txt}{ralign 78:(Std. Err. adjusted for {res:1,113} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1071828{col 26}{space 2}  .064374{col 37}{space 1}   -1.67{col 46}{space 3}0.096{col 54}{space 4} -.233491{col 67}{space 3} .0191254
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2315096{col 26}{space 2} .0623256{col 37}{space 1}   -3.71{col 46}{space 3}0.000{col 54}{space 4}-.3537987{col 67}{space 3}-.1092205
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2015394{col 26}{space 2} .0607139{col 37}{space 1}   -3.32{col 46}{space 3}0.001{col 54}{space 4}-.3206662{col 67}{space 3}-.0824127
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .1201205{col 26}{space 2} .0618668{col 37}{space 1}    1.94{col 46}{space 3}0.052{col 54}{space 4}-.0012683{col 67}{space 3} .2415093
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2845193{col 26}{space 2} .0644699{col 37}{space 1}   -4.41{col 46}{space 3}0.000{col 54}{space 4}-.4110157{col 67}{space 3}-.1580229
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1847897{col 26}{space 2} .0647377{col 37}{space 1}   -2.85{col 46}{space 3}0.004{col 54}{space 4}-.3118115{col 67}{space 3} -.057768
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2553682{col 26}{space 2}  .064129{col 37}{space 1}   -3.98{col 46}{space 3}0.000{col 54}{space 4}-.3811957{col 67}{space 3}-.1295407
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1903446{col 26}{space 2} .0617601{col 37}{space 1}   -3.08{col 46}{space 3}0.002{col 54}{space 4}-.3115241{col 67}{space 3}-.0691651
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  4.17778{col 26}{space 2} .0934085{col 37}{space 1}   44.73{col 46}{space 3}0.000{col 54}{space 4} 3.994503{col 67}{space 3} 4.361057
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     2,226
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.4961973 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.5038027 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4981884 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5018116 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5254843 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4745157 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5171153 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4828847 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5274708 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4725292 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5108806 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4891194 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4935466 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5064534 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 4}.490907 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 4}.509093 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.572914{col 26}{space 2}  .046428{col 37}{space 1}   76.96{col 46}{space 3}0.000{col 54}{space 4} 3.481916{col 67}{space 3} 3.663911
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.465731{col 26}{space 2} .0442689{col 37}{space 1}   78.29{col 46}{space 3}0.000{col 54}{space 4} 3.378965{col 67}{space 3} 3.552496
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.635089{col 26}{space 2} .0447161{col 37}{space 1}   81.29{col 46}{space 3}0.000{col 54}{space 4} 3.547447{col 67}{space 3} 3.722731
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.403579{col 26}{space 2} .0445495{col 37}{space 1}   76.40{col 46}{space 3}0.000{col 54}{space 4} 3.316264{col 67}{space 3} 3.490895
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.614548{col 26}{space 2} .0437274{col 37}{space 1}   82.66{col 46}{space 3}0.000{col 54}{space 4} 3.528844{col 67}{space 3} 3.700252
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.413009{col 26}{space 2} .0443976{col 37}{space 1}   76.87{col 46}{space 3}0.000{col 54}{space 4} 3.325991{col 67}{space 3} 3.500026
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.653358{col 26}{space 2} .0441444{col 37}{space 1}   82.76{col 46}{space 3}0.000{col 54}{space 4} 3.566837{col 67}{space 3}  3.73988
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.368839{col 26}{space 2} .0466656{col 37}{space 1}   72.19{col 46}{space 3}0.000{col 54}{space 4} 3.277376{col 67}{space 3} 3.460302
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.609299{col 26}{space 2} .0439126{col 37}{space 1}   82.19{col 46}{space 3}0.000{col 54}{space 4} 3.523232{col 67}{space 3} 3.695366
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.424509{col 26}{space 2} .0470565{col 37}{space 1}   72.77{col 46}{space 3}0.000{col 54}{space 4}  3.33228{col 67}{space 3} 3.516738
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.46091{col 26}{space 2} .0444348{col 37}{space 1}   77.89{col 46}{space 3}0.000{col 54}{space 4}  3.37382{col 67}{space 3} 3.548001
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.581031{col 26}{space 2} .0444874{col 37}{space 1}   80.50{col 46}{space 3}0.000{col 54}{space 4} 3.493837{col 67}{space 3} 3.668224
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.648247{col 26}{space 2} .0447138{col 37}{space 1}   81.59{col 46}{space 3}0.000{col 54}{space 4} 3.560609{col 67}{space 3} 3.735884
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.392878{col 26}{space 2} .0457958{col 37}{space 1}   74.09{col 46}{space 3}0.000{col 54}{space 4}  3.30312{col 67}{space 3} 3.482637
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.615818{col 26}{space 2} .0438637{col 37}{space 1}   82.43{col 46}{space 3}0.000{col 54}{space 4} 3.529846{col 67}{space 3} 3.701789
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.425473{col 26}{space 2} .0449736{col 37}{space 1}   76.17{col 46}{space 3}0.000{col 54}{space 4} 3.337326{col 67}{space 3}  3.51362
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_women
{txt}
{com}. 
. coefplot support_men support_women, xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}") drop(_cons)
{res}{txt}
{com}. 
. 
. ************
. * Appendix *
. ************
. 
. *Figure A1: Argentina by age
. graph bar (percent) count_obs if qcountry==2, over(age_grp_all) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A2: Kenya by age
. graph bar (percent) count_obs if qcountry==1, over(age_grp_all) scheme(plotplainblind) legend(off) 
{res}{txt}
{com}. 
. *Figure A3: Pakistan by age
. graph bar (percent) count_obs if qcountry==3, over(age_grp_all) scheme(plotplainblind) legend(off) 
{res}{txt}
{com}. 
. *Figure A4: Argentina by gender
. graph bar (percent) count_obs if qcountry==2, over(gender_all) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A5: Kenya by gender
. graph bar (percent) count_obs if qcountry==1, over(gender_all) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A6: Pakistan by age
. graph bar (percent) count_obs if qcountry==3, over(gender_all) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A7: Argentina by education
. graph bar (percent) count_obs, over(education_Ar) scheme(plotplainblind) legend(off) 
{res}{txt}
{com}. 
. *Figure A8: Kenya by education
. graph bar (percent) count_obs, over(DEM4_Ken) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A9: Pakistan by education
. graph bar (percent) count_obs, over(education_Pak) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A10: Argentina by income
. graph bar (percent) count_obs, over(income_Ar) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A11: Kenya by income
. graph bar (percent) count_obs, over(income_Ken) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A12: Pakistan by income
. graph bar (percent) count_obs, over(income_Pak) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A13: weights Argentina
. hist weight if qcountry==2, scheme(plotplainblind) xlabel(0(1)5) frac
{txt}(bin={res}33{txt}, start={res}.78656314{txt}, width={res}.11257891{txt})
{res}{txt}
{com}. 
. *Figure A14: weights Kenya
. hist weight if qcountry==1, scheme(plotplainblind) xlabel(0(1)5) frac
{txt}(bin={res}30{txt}, start={res}.80952613{txt}, width={res}.04308116{txt})
{res}{txt}
{com}. 
. *Figure A15: weights Pakistan
. hist weight if qcountry==3, scheme(plotplainblind) xlabel(0(1)5) frac
{txt}(bin={res}33{txt}, start={res}.68489197{txt}, width={res}.01954209{txt})
{res}{txt}
{com}. 
. *Table A16: comparing sample with other LMICs in World Value Survey 2017-2022
. use "WVS_TimeSeries_4_0.dta", clear
{txt}
{com}. keep if S002VS==7
{txt}(356,591 observations deleted)

{com}. gen hic=1 if COUNTRY_ALPHA=="DEU"
{txt}(92,750 missing values generated)

{com}. replace hic=1 if COUNTRY_ALPHA=="AUS"
{txt}(1,813 real changes made)

{com}. replace hic=1 if COUNTRY_ALPHA=="CAN"
{txt}(4,018 real changes made)

{com}. replace hic=1 if COUNTRY_ALPHA=="KOR"
{txt}(1,245 real changes made)

{com}. replace hic=1 if COUNTRY_ALPHA=="NLD"
{txt}(2,145 real changes made)

{com}. replace hic=1 if COUNTRY_ALPHA=="NZL"
{txt}(1,057 real changes made)

{com}. replace hic=1 if COUNTRY_ALPHA=="SGP"
{txt}(2,012 real changes made)

{com}. replace hic=1 if COUNTRY_ALPHA=="USA"
{txt}(2,596 real changes made)

{com}. replace hic=1 if COUNTRY_ALPHA=="TWN"
{txt}(1,223 real changes made)

{com}. 
. replace hic=0 if missing(hic)
{txt}(76,641 real changes made)

{com}. 
. drop if hic==1
{txt}(17,637 observations deleted)

{com}. 
. gen survey_countries=1 if COUNTRY_ALPHA=="KEN"
{txt}(75,375 missing values generated)

{com}. replace survey_countries=1 if COUNTRY_ALPHA=="ARG"
{txt}(1,003 real changes made)

{com}. replace survey_countries=1 if COUNTRY_ALPHA=="PAK"
{txt}(1,995 real changes made)

{com}. replace survey_countries=0 if missing(survey_countries)
{txt}(72,377 real changes made)

{com}. 
. replace C001=. if C001<0
{txt}(529 real changes made, 529 to missing)

{com}. replace C001=4 if C001==3
{txt}(11,232 real changes made)

{com}. replace C001=3 if C001==2
{txt}(31,395 real changes made)

{com}. replace C001=2 if C001==4
{txt}(11,232 real changes made)

{com}. 
. replace E224=. if E224<0
{txt}(2,508 real changes made, 2,508 to missing)

{com}. replace B008=. if B008<0
{txt}(3,361 real changes made, 3,361 to missing)

{com}. replace B008=. if B008==3
{txt}(2,289 real changes made, 2,289 to missing)

{com}. 
. replace E069_45=. if E069_45<0
{txt}(15,757 real changes made, 15,757 to missing)

{com}. replace E268=. if E069_45<0
{txt}(0 real changes made)

{com}. replace E035=. if E069_45<0
{txt}(0 real changes made)

{com}. replace E036=. if E069_45<0
{txt}(0 real changes made)

{com}. 
. *E224 tax the rich to help poor
. *C001 men more right to job than women
. *B008 environment versus econ growth
. *E069_45 IMF confidence
. *E268 Corruption
. *E035 income inequality
. *E036 private ownership
. 
. replace E035=abs(E035-10)
{txt}(67,408 real changes made)

{com}. replace E036=abs(E036-10)
{txt}(62,581 real changes made)

{com}. replace B008=abs(B008-2)
{txt}(29,992 real changes made)

{com}. 
. gen sd_C001=C001
{txt}(529 missing values generated)

{com}. gen sd_E224=E224
{txt}(2,508 missing values generated)

{com}. gen sd_B008=B008
{txt}(5,650 missing values generated)

{com}. gen sd_E069_45=E069_45
{txt}(15,757 missing values generated)

{com}. gen sd_E035=E035
{txt}
{com}. gen sd_E036=E036
{txt}
{com}. gen sd_E268=E268
{txt}
{com}. 
. gen total=1
{txt}
{com}. egen countries=group(COUNTRY_ALPHA)
{txt}
{com}. 
. collapse (mean) C001 E224 B008 E069_45 E268 E035 E036 (sd) sd_C001 sd_E224 sd_B008 sd_E069_45 sd_E035 sd_E036 sd_E268 (sum) total (count) countries, by(survey_countries)
{txt}
{com}. 
. foreach x of varlist C001 E224 B008 E069_45 E268 E035 E036  {c -(}
{txt}  2{com}. rename `x' mean_`x'
{txt}  3{com}. 
. {c )-}
{res}{txt}
{com}. 
. reshape long mean_, i(survey_countries) j(variables, string)
{txt}(note: j = B008 C001 E035 E036 E069_45 E224 E268)

Data{col 36}wide{col 43}->{col 48}long
{hline 77}
Number of obs.                 {res}       2   {txt}->{res}      14
{txt}Number of variables            {res}      17   {txt}->{res}      12
{txt}j variable (7 values)                     ->   {res}variables
{txt}xij variables:
      {res}mean_B008 mean_C001 ... mean_E268   {txt}->   {res}mean_
{txt}{hline 77}

{com}. 
. gen sd_=sd_C001 if variables=="C001"
{txt}(12 missing values generated)

{com}. replace sd_=sd_E224 if variables=="E224"
{txt}(2 real changes made)

{com}. replace sd_=sd_B008 if variables=="B008"
{txt}(2 real changes made)

{com}. replace sd_=sd_E069_45 if variables=="E069_45"
{txt}(2 real changes made)

{com}. replace sd_=sd_E035 if variables=="E035"
{txt}(2 real changes made)

{com}. replace sd_=sd_E036 if variables=="E036"
{txt}(2 real changes made)

{com}. replace sd_=sd_E268 if variables=="E268"
{txt}(2 real changes made)

{com}. 
. drop sd_C001 sd_E224 sd_B008 sd_E069_45 sd_E035 sd_E036 sd_E268 countries
{txt}
{com}. gen id=1
{txt}
{com}. reshape wide mean_ sd_ total, i(variables) j(survey_countries)
{txt}(note: j = 0 1)

Data{col 36}long{col 43}->{col 48}wide
{hline 77}
Number of obs.                 {res}      14   {txt}->{res}       7
{txt}Number of variables            {res}       6   {txt}->{res}       8
{txt}j variable (2 values)  {res}survey_countries   {txt}->   (dropped)
xij variables:
                                  {res}mean_   {txt}->   {res}mean_0 mean_1
                                    sd_   {txt}->   {res}sd_0 sd_1
                                  total   {txt}->   {res}total0 total1
{txt}{hline 77}

{com}. drop id
{txt}
{com}. order variables mean_1 sd_1 total1 mean_0 sd_0 total0
{txt}
{com}. rename mean_1 mean_included
{res}{txt}
{com}. rename sd_1 sd_included
{res}{txt}
{com}. rename total1 n_included
{res}{txt}
{com}. rename mean_0 mean_not_included
{res}{txt}
{com}. rename sd_0 sd_not_included
{res}{txt}
{com}. rename total0 n_not_included
{res}{txt}
{com}. gen varname="IMF confidence" if variables=="E069_45"
{txt}(6 missing values generated)

{com}. replace varname="Private ownership" if variables=="E036"
{txt}variable {bf}varname{sf} was {bf}{res}str14{sf}{txt} now {bf}{res}str17{sf}
{txt}(1 real change made)

{com}. replace varname="Corruption" if variables=="E268"
{txt}(1 real change made)

{com}. replace varname="Address income inequality" if variables=="E035"
{txt}variable {bf}varname{sf} was {bf}{res}str17{sf}{txt} now {bf}{res}str25{sf}
{txt}(1 real change made)

{com}. replace varname="Gender equality" if variables=="C001"
{txt}(1 real change made)

{com}. replace varname="Environment" if variables=="B008"
{txt}(1 real change made)

{com}. drop if variables=="E224"
{txt}(1 observation deleted)

{com}. order varname
{txt}
{com}. gen sort=1 if varname=="IMF confidence"
{txt}(5 missing values generated)

{com}. replace sort=2 if varname=="Private ownership"
{txt}(1 real change made)

{com}. replace sort=3 if varname=="Corruption"
{txt}(1 real change made)

{com}. replace sort=4 if varname=="Address income inequality"
{txt}(1 real change made)

{com}. replace sort=5 if varname=="Gender equality"
{txt}(1 real change made)

{com}. replace sort=6 if varname=="Environment"
{txt}(1 real change made)

{com}. sort sort
{txt}
{com}. drop sort
{txt}
{com}. gen difference=mean_included-mean_not_included
{txt}
{com}. gen difference_percent=(difference/mean_included)*100
{txt}
{com}. 
. export excel using "TableA16.xlsx", firstrow(variables)
{res}{txt}file {bf:TableA16.xlsx} saved

{com}. 
. *Table A17: Comparing internet users in Kenya with non-internet users in World Value Survey 
. use "WVS_TimeSeries_4_0.dta", clear
{txt}
{com}. keep if S002VS==7
{txt}(356,591 observations deleted)

{com}. 
. keep if COUNTRY_ALPHA=="KEN"
{txt}(93,012 observations deleted)

{com}. 
. replace C001=. if C001<0
{txt}(5 real changes made, 5 to missing)

{com}. replace C001=4 if C001==3
{txt}(160 real changes made)

{com}. replace C001=3 if C001==2
{txt}(637 real changes made)

{com}. replace C001=2 if C001==4
{txt}(160 real changes made)

{com}. 
. replace E224=. if E224<0
{txt}(31 real changes made, 31 to missing)

{com}. replace B008=. if B008<0
{txt}(51 real changes made, 51 to missing)

{com}. replace B008=. if B008==3
{txt}(1 real change made, 1 to missing)

{com}. 
. replace E069_45=. if E069_45<0
{txt}(149 real changes made, 149 to missing)

{com}. replace E268=. if E069_45<0
{txt}(0 real changes made)

{com}. replace E035=. if E069_45<0
{txt}(0 real changes made)

{com}. replace E036=. if E069_45<0
{txt}(0 real changes made)

{com}. 
. *E224 tax the rich to help poor
. *C001 men more right to job than women
. *B008 environment versus econ growth
. *E069_45 IMF confidence
. *E268 Corruption
. *E035 income inequality
. *E036 private ownership
. 
. replace E035=abs(E035-10)
{txt}(1,110 real changes made)

{com}. replace E036=abs(E036-10)
{txt}(1,082 real changes made)

{com}. replace B008=abs(B008-2)
{txt}(645 real changes made)

{com}. 
. gen sd_C001=C001
{txt}(5 missing values generated)

{com}. gen sd_E224=E224
{txt}(31 missing values generated)

{com}. gen sd_B008=B008
{txt}(52 missing values generated)

{com}. gen sd_E069_45=E069_45
{txt}(149 missing values generated)

{com}. gen sd_E035=E035
{txt}
{com}. gen sd_E036=E036
{txt}
{com}. gen sd_E268=E268
{txt}
{com}. 
. gen total=1
{txt}
{com}. egen countries=group(COUNTRY_ALPHA)
{txt}
{com}. 
. gen internet=1 if E262B==5
{txt}(1,082 missing values generated)

{com}. replace internet=0 if missing(internet)
{txt}(1,082 real changes made)

{com}. replace internet=. if E262B<0
{txt}(26 real changes made, 26 to missing)

{com}. 
. collapse (mean) C001 E224 B008 E069_45 E268 E035 E036 (sd) sd_C001 sd_E224 sd_B008 sd_E069_45 sd_E035 sd_E036 sd_E268 (sum) total , by(internet)
{txt}
{com}. 
. drop if missing(internet)
{txt}(1 observation deleted)

{com}. replace internet=2 if internet==0
{txt}(1 real change made)

{com}. replace internet=internet-1
{txt}(2 real changes made)

{com}. 
. foreach x of varlist C001 E224 B008 E069_45 E268 E035 E036  {c -(}
{txt}  2{com}. rename `x' mean_`x'
{txt}  3{com}. 
. {c )-}
{res}{txt}
{com}. 
. reshape long mean_, i(internet) j(variables, string)
{txt}(note: j = B008 C001 E035 E036 E069_45 E224 E268)

Data{col 36}wide{col 43}->{col 48}long
{hline 77}
Number of obs.                 {res}       2   {txt}->{res}      14
{txt}Number of variables            {res}      16   {txt}->{res}      11
{txt}j variable (7 values)                     ->   {res}variables
{txt}xij variables:
      {res}mean_B008 mean_C001 ... mean_E268   {txt}->   {res}mean_
{txt}{hline 77}

{com}. 
. gen sd_=sd_C001 if variables=="C001"
{txt}(12 missing values generated)

{com}. replace sd_=sd_E224 if variables=="E224"
{txt}(2 real changes made)

{com}. replace sd_=sd_B008 if variables=="B008"
{txt}(2 real changes made)

{com}. replace sd_=sd_E069_45 if variables=="E069_45"
{txt}(2 real changes made)

{com}. replace sd_=sd_E035 if variables=="E035"
{txt}(2 real changes made)

{com}. replace sd_=sd_E036 if variables=="E036"
{txt}(2 real changes made)

{com}. replace sd_=sd_E268 if variables=="E268"
{txt}(2 real changes made)

{com}. 
. drop sd_C001 sd_E224 sd_B008 sd_E069_45 sd_E035 sd_E036 sd_E268
{txt}
{com}. gen id=1
{txt}
{com}. reshape wide mean_ sd_ total, i(variables) j(internet)
{txt}(note: j = 0 1)

Data{col 36}long{col 43}->{col 48}wide
{hline 77}
Number of obs.                 {res}      14   {txt}->{res}       7
{txt}Number of variables            {res}       6   {txt}->{res}       8
{txt}j variable (2 values)          {res}internet   {txt}->   (dropped)
xij variables:
                                  {res}mean_   {txt}->   {res}mean_0 mean_1
                                    sd_   {txt}->   {res}sd_0 sd_1
                                  total   {txt}->   {res}total0 total1
{txt}{hline 77}

{com}. drop id
{txt}
{com}. order variables mean_1 sd_1 total1 mean_0 sd_0 total0
{txt}
{com}. rename mean_1 mean_internet
{res}{txt}
{com}. rename sd_1 sd_internet
{res}{txt}
{com}. rename total1 n_internet
{res}{txt}
{com}. rename mean_0 mean_no_internet
{res}{txt}
{com}. rename sd_0 sd_no_internet
{res}{txt}
{com}. rename total0 n_no_internet
{res}{txt}
{com}. gen varname="IMF confidence" if variables=="E069_45"
{txt}(6 missing values generated)

{com}. replace varname="Private ownership" if variables=="E036"
{txt}variable {bf}varname{sf} was {bf}{res}str14{sf}{txt} now {bf}{res}str17{sf}
{txt}(1 real change made)

{com}. replace varname="Corruption" if variables=="E268"
{txt}(1 real change made)

{com}. replace varname="Address income inequality" if variables=="E035"
{txt}variable {bf}varname{sf} was {bf}{res}str17{sf}{txt} now {bf}{res}str25{sf}
{txt}(1 real change made)

{com}. replace varname="Gender equality" if variables=="C001"
{txt}(1 real change made)

{com}. replace varname="Environment" if variables=="B008"
{txt}(1 real change made)

{com}. drop if variables=="E224"
{txt}(1 observation deleted)

{com}. order varname
{txt}
{com}. gen sort=1 if varname=="IMF confidence"
{txt}(5 missing values generated)

{com}. replace sort=2 if varname=="Private ownership"
{txt}(1 real change made)

{com}. replace sort=3 if varname=="Corruption"
{txt}(1 real change made)

{com}. replace sort=4 if varname=="Address income inequality"
{txt}(1 real change made)

{com}. replace sort=5 if varname=="Gender equality"
{txt}(1 real change made)

{com}. replace sort=6 if varname=="Environment"
{txt}(1 real change made)

{com}. sort sort
{txt}
{com}. drop sort
{txt}
{com}. gen difference=mean_internet-mean_no_internet
{txt}
{com}. gen difference_percent=(difference/mean_internet)*100
{txt}
{com}. 
. export excel using "TableA17.xlsx", firstrow(variables)
{res}{txt}file {bf:TableA17.xlsx} saved

{com}. 
. *Figure A19: ideology Argentina
. use  "IMF_survey_experiment.dta", clear
{txt}(File created by user 'sujoy.das' at Wed Jun  7 18:44:55 2023)

{com}. 
. graph bar (percent) count_obs if qcountry==2, over(q4) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A20: ideology Kenya
. graph bar (percent) count_obs if qcountry==1, over(q4) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A21: ideology Pakistan
. graph bar (percent) count_obs if qcountry==3, over(q4) scheme(plotplainblind) legend(off)
{res}{txt}
{com}. 
. *Figure A22: ideology and gender discrimination
. use "WVS_TimeSeries_4_0.dta", clear
{txt}
{com}. 
. keep S002VS S003 COUNTRY_ALPHA S017 S020 E033 C001 D057 D058 D060 F199 E035 E036 E037 
{txt}
{com}. rename S002VS wave
{res}{txt}
{com}. rename S003 country
{res}{txt}
{com}. rename COUNTR iso3
{res}{txt}
{com}. rename S020 year
{res}{txt}
{com}. order country iso3 year wave 
{txt}
{com}. 
. replace iso3="ADO" if iso3=="AND"
{txt}(2,007 real changes made)

{com}. replace iso3="WBG" if iso3=="PSE"
{txt}(1,000 real changes made)

{com}. replace iso3="ROM" if iso3=="ROU"
{txt}(5,775 real changes made)

{com}. sort iso3 
{txt}
{com}. merge iso3 using "Countries-iso3-unique"
{txt}{p}
(note: you are using old
{bf:merge} syntax; see
{bf:{help merge:[D] merge}} for new syntax)
{p_end}
{p 0 4 2}
variable{txt} iso3
does not uniquely identify observations in
the master data
{p_end}
{p 0 7 2}
(note: variable
country was str48 in the using data, but will be
int now)
{p_end}
{p 0 4 2}
variable{txt} iso3
does not uniquely identify observations in
Countries-iso3-unique.dta
{p_end}

{com}. tab _m 

     {txt}_merge {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        447        0.10        0.10
{txt}          2 {c |}{res}        163        0.04        0.14
{txt}          3 {c |}{res}    450,422       99.86      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}    451,032      100.00
{txt}
{com}. drop if _m==2
{txt}(163 observations deleted)

{com}. drop _m ifs iso2 vpu isor* cow
{txt}
{com}. 
. g lr=E033 if E033>0 & E033<11
{txt}(127,994 missing values generated)

{com}. g gn_jobs=C001==1 if C001>0 & C001<4
{txt}(31,027 missing values generated)

{com}. g gn_hwife=D057==1|D057==2 if D057>0 & D057<5
{txt}(50,726 missing values generated)

{com}. g gn_uneq=D058==3|D058==4 if D058>0 & D058<5
{txt}(301,101 missing values generated)

{com}. g gn_uni=D060==1|D060==2 if D060>0 & D060<5
{txt}(64,130 missing values generated)

{com}. g gn_beat=F199-1 if F199>0 & F199<11
{txt}(200,567 missing values generated)

{com}. 
. su lr gn_*

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 10}lr {c |}{res}    322,875    5.673672    2.386816          1         10
{txt}{space 5}gn_jobs {c |}{res}    419,842    .3907279    .4879141          0          1
{txt}{space 4}gn_hwife {c |}{res}    400,143    .6415456    .4795471          0          1
{txt}{space 5}gn_uneq {c |}{res}    149,768    .1557476    .3626171          0          1
{txt}{space 6}gn_uni {c |}{res}    386,739    .2412816    .4278613          0          1
{txt}{hline 13}{c +}{hline 57}
{space 5}gn_beat {c |}{res}    250,302    .9415826    1.989338          0          9
{txt}
{com}. corr gn_jobs gn_hw gn_uni gn_beat
{txt}(obs=229,119)

             {c |}  gn_jobs gn_hwife   gn_uni  gn_beat
{hline 13}{c +}{hline 36}
     gn_jobs {c |}{res}   1.0000
    {txt}gn_hwife {c |}{res}   0.1229   1.0000
      {txt}gn_uni {c |}{res}   0.3076   0.1272   1.0000
     {txt}gn_beat {c |}{res}   0.0947  -0.0242   0.1493   1.0000

{txt}
{com}. factor gn_jobs gn_hw gn_uni gn_beat
{txt}(obs=229,119)

Factor analysis/correlation{col 50}Number of obs    = {res}   229,119
{col 5}{txt}Method: principal factors{col 50}Retained factors =   {res}       2
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       6

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      0.53425      0.48065            1.9345       1.9345
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.05361      0.16005            0.1941       2.1286
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}     -0.10644      0.09880           -0.3854       1.7432
{txt}{col 5}{ralign 11:Factor4}  {c |}{res}     -0.20524            .           -0.7432       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}6{txt})  ={res} 3.5e+04{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:gn_jobs}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4552}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0183}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.7924}}}{space 1}
{space 4}{space 0}{ralign 12:gn_hwife}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.2204}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1590}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.9262}}}{space 1}
{space 4}{space 0}{ralign 12:gn_uni}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4814}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0153}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.7680}}}{space 1}
{space 4}{space 0}{ralign 12:gn_beat}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.2162}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1666}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.9255}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. 
. g c001=2*(C001==1)+1*(C001==3) if C001>0
{txt}(31,027 missing values generated)

{com}. g d057=4-D057 if D057>0
{txt}(50,726 missing values generated)

{com}. g d060=4-D060 if D060>0
{txt}(64,130 missing values generated)

{com}. g f199=F199-1 if F199>0
{txt}(200,567 missing values generated)

{com}. corr c001 d057 d060 f199
{txt}(obs=229,119)

             {c |}     c001     d057     d060     f199
{hline 13}{c +}{hline 36}
        c001 {c |}{res}   1.0000
        {txt}d057 {c |}{res}   0.1449   1.0000
        {txt}d060 {c |}{res}   0.3463   0.1665   1.0000
        {txt}f199 {c |}{res}   0.1208  -0.0205   0.1523   1.0000

{txt}
{com}. su c001 d057 d060 f199

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}c001 {c |}{res}    419,842    .9486712    .9111268          0          2
{txt}{space 8}d057 {c |}{res}    400,143    1.795166    .9030703          0          3
{txt}{space 8}d060 {c |}{res}    386,739    1.020944    .9146688          0          3
{txt}{space 8}f199 {c |}{res}    250,302    .9415826    1.989338          0          9
{txt}
{com}. 
. g gn_disc=c001+d057+d060+f199
{txt}(221,750 missing values generated)

{com}. hist gn_disc
{txt}(bin={res}53{txt}, start={res}0{txt}, width={res}.32075472{txt})
{res}{txt}
{com}. bys year: su gn_disc

{txt}{hline}
-> year = 1981

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1982

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1984

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1989

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1990

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1991

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1995

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1996

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1997

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1998

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 1999

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 2000

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 2001

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 2002

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 2003

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 2004

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 2005

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}     11,577    3.742334    2.304228          0         17

{txt}{hline}
-> year = 2006

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}     29,143    4.226161    2.818317          0         17

{txt}{hline}
-> year = 2007

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}     17,859    4.774623    3.322898          0         17

{txt}{hline}
-> year = 2008

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}          0

{txt}{hline}
-> year = 2009

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}      2,156    4.137755     1.83142          0         12

{txt}{hline}
-> year = 2010

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}      4,492    4.529163     2.32445          0         17

{txt}{hline}
-> year = 2011

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}     23,012    4.565618    2.637599          0         17

{txt}{hline}
-> year = 2012

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}     26,763    4.709076    2.897721          0         17

{txt}{hline}
-> year = 2013

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}     15,986    5.435819     3.44453          0         17

{txt}{hline}
-> year = 2014

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}      9,703    5.235494    2.964347          0         17

{txt}{hline}
-> year = 2016

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}      1,901    7.557601    4.020143          0         17

{txt}{hline}
-> year = 2017

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}      9,126    3.955731    2.662991          0         17

{txt}{hline}
-> year = 2018

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}     38,953    4.657485    2.763855          0         17

{txt}{hline}
-> year = 2019

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}      6,487    5.118391    2.773411          0         17

{txt}{hline}
-> year = 2020

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}     20,491    4.600996    2.859742          0         17

{txt}{hline}
-> year = 2021

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}      5,767    4.729669    3.056627          0         17

{txt}{hline}
-> year = 2022

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}gn_disc {c |}{res}      5,703     3.90619    2.742382          0         17

{txt}
{com}. 
. corr lr gn_disc if year>=2012 & iso3=="ARG"|iso3=="PAK"|iso3=="KEN"
{txt}(obs=3,725)

             {c |}       lr  gn_disc
{hline 13}{c +}{hline 18}
          lr {c |}{res}   1.0000
     {txt}gn_disc {c |}{res}   0.0431   1.0000

{txt}
{com}. 
. twoway scatter (gn_disc lr) if year>=2012 & iso3=="ARG"|iso3=="PAK"|iso3=="KEN", scheme(s1mono) ytitle(Gender discrimination index) xtitle(Left-right positioning) xsc(range(1(2)11))
{res}{txt}
{com}. 
. pwcorr lr gn_disc if year==2017 & iso3=="ARG", sig   

             {txt}{c |}       lr  gn_disc
{hline 13}{c +}{hline 18}
          lr {c |} {res}  1.0000 
             {txt}{c |}
             {c |}
     gn_disc {c |} {res}  0.1261   1.0000 
             {txt}{c |}{res}   0.0006
             {txt}{c |}

{com}. pwcorr lr gn_disc if year==2012 & iso3=="PAK", sig   

             {txt}{c |}       lr  gn_disc
{hline 13}{c +}{hline 18}
          lr {c |} {res}  1.0000 
             {txt}{c |}
             {c |}
     gn_disc {c |} {res} -0.0751   1.0000 
             {txt}{c |}{res}   0.0115
             {txt}{c |}

{com}. pwcorr lr gn_disc if year==2021 & iso3=="KEN", sig   

             {txt}{c |}       lr  gn_disc
{hline 13}{c +}{hline 18}
          lr {c |} {res}  1.0000 
             {txt}{c |}
             {c |}
     gn_disc {c |} {res} -0.0635   1.0000 
             {txt}{c |}{res}   0.0354
             {txt}{c |}

{com}. 
. *Figure A23: ideology and gender discrimination by country
. twoway scatter (gn_disc lr) if year>=2012 & iso3=="ARG", scheme(s1mono) ytitle(Gender discrimination index) xtitle(Left-right positioning) xsc(range(1(2)11))
{res}{txt}
{com}. twoway scatter (gn_disc lr) if year>=2012 & iso3=="PAK", scheme(s1mono) ytitle(Gender discrimination index) xtitle(Left-right positioning) xsc(range(1(2)11))
{res}{txt}
{com}. twoway scatter (gn_disc lr) if year>=2012 & iso3=="KEN", scheme(s1mono) ytitle(Gender discrimination index) xtitle(Left-right positioning) xsc(range(1(2)11))
{res}{txt}
{com}. 
. *Figure A24: Separate results by country
. use  "IMF_survey_experiment.dta", clear
{txt}(File created by user 'sujoy.das' at Wed Jun  7 18:44:55 2023)

{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] if qcountry==1, absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     1,078
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}    538{txt}){col 67}= {res}     11.15
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0870
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0802
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0870
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}       539{txt}{col 51}Root MSE{col 67}= {res}    1.4949

{txt}{ralign 78:(Std. Err. adjusted for {res:539} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2594239{col 26}{space 2} .0942227{col 37}{space 1}   -2.75{col 46}{space 3}0.006{col 54}{space 4}-.4445135{col 67}{space 3}-.0743344
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1187096{col 26}{space 2} .0951436{col 37}{space 1}   -1.25{col 46}{space 3}0.213{col 54}{space 4}-.3056082{col 67}{space 3} .0681889
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3017503{col 26}{space 2} .0934987{col 37}{space 1}   -3.23{col 46}{space 3}0.001{col 54}{space 4}-.4854177{col 67}{space 3} -.118083
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0372687{col 26}{space 2} .0969838{col 37}{space 1}   -0.38{col 46}{space 3}0.701{col 54}{space 4} -.227782{col 67}{space 3} .1532447
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.5926368{col 26}{space 2} .0952291{col 37}{space 1}   -6.22{col 46}{space 3}0.000{col 54}{space 4}-.7797032{col 67}{space 3}-.4055705
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2055252{col 26}{space 2} .0958988{col 37}{space 1}   -2.14{col 46}{space 3}0.033{col 54}{space 4}-.3939072{col 67}{space 3}-.0171433
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.432553{col 26}{space 2} .0965586{col 37}{space 1}   -4.48{col 46}{space 3}0.000{col 54}{space 4}-.6222311{col 67}{space 3} -.242875
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2545614{col 26}{space 2} .0930878{col 37}{space 1}   -2.73{col 46}{space 3}0.006{col 54}{space 4}-.4374214{col 67}{space 3}-.0717013
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.993487{col 26}{space 2} .1368808{col 37}{space 1}   36.48{col 46}{space 3}0.000{col 54}{space 4} 4.724601{col 67}{space 3} 5.262374
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        1{col 27}{space 1}        0{col 39}{result}{space 1}        1{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     1,078
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.4877576 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.5122424 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.5093751 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.4906249 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.4994687 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.5005313 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5183239 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4816761 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 4}.509473 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 4}.490527 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5002608 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4997392 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4845593 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5154407 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5059059 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4940941 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 4.024112{col 26}{space 2} .0634314{col 37}{space 1}   63.44{col 46}{space 3}0.000{col 54}{space 4} 3.899789{col 67}{space 3} 4.148436
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.764688{col 26}{space 2} .0635125{col 37}{space 1}   59.27{col 46}{space 3}0.000{col 54}{space 4} 3.640206{col 67}{space 3} 3.889171
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.949466{col 26}{space 2} .0626285{col 37}{space 1}   63.06{col 46}{space 3}0.000{col 54}{space 4} 3.826717{col 67}{space 3} 4.072216
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.830757{col 26}{space 2} .0650333{col 37}{space 1}   58.90{col 46}{space 3}0.000{col 54}{space 4} 3.703294{col 67}{space 3} 3.958219
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  4.04226{col 26}{space 2} .0607427{col 37}{space 1}   66.55{col 46}{space 3}0.000{col 54}{space 4} 3.923206{col 67}{space 3} 4.161313
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.740509{col 26}{space 2} .0655897{col 37}{space 1}   57.03{col 46}{space 3}0.000{col 54}{space 4} 3.611956{col 67}{space 3} 3.869063
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 4.181929{col 26}{space 2} .0627761{col 37}{space 1}   66.62{col 46}{space 3}0.000{col 54}{space 4}  4.05889{col 67}{space 3} 4.304968
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.589292{col 26}{space 2} .0649493{col 37}{space 1}   55.26{col 46}{space 3}0.000{col 54}{space 4} 3.461993{col 67}{space 3}  3.71659
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.993933{col 26}{space 2} .0613362{col 37}{space 1}   65.12{col 46}{space 3}0.000{col 54}{space 4} 3.873717{col 67}{space 3}  4.11415
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.788408{col 26}{space 2} .0667672{col 37}{space 1}   56.74{col 46}{space 3}0.000{col 54}{space 4} 3.657547{col 67}{space 3} 3.919269
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.909176{col 26}{space 2} .0641398{col 37}{space 1}   60.95{col 46}{space 3}0.000{col 54}{space 4} 3.783464{col 67}{space 3} 4.034887
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.871907{col 26}{space 2}  .064865{col 37}{space 1}   59.69{col 46}{space 3}0.000{col 54}{space 4} 3.744774{col 67}{space 3}  3.99904
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  4.11418{col 26}{space 2} .0627701{col 37}{space 1}   65.54{col 46}{space 3}0.000{col 54}{space 4} 3.991153{col 67}{space 3} 4.237207
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.681627{col 26}{space 2} .0657773{col 37}{space 1}   55.97{col 46}{space 3}0.000{col 54}{space 4} 3.552706{col 67}{space 3} 3.810548
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 4.017002{col 26}{space 2} .0646437{col 37}{space 1}   62.14{col 46}{space 3}0.000{col 54}{space 4} 3.890302{col 67}{space 3} 4.143701
{txt}{space 9}No  {c |}{col 14}{res}{space 2}  3.76244{col 26}{space 2} .0613984{col 37}{space 1}   61.28{col 46}{space 3}0.000{col 54}{space 4} 3.642101{col 67}{space 3} 3.882779
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_kenya
{txt}
{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] if qcountry==2, absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,206
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   1102{txt}){col 67}= {res}      6.65
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0267
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0232
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0267
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     1,103{txt}{col 51}Root MSE{col 67}= {res}    1.4868

{txt}{ralign 78:(Std. Err. adjusted for {res:1,103} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1556012{col 26}{space 2} .0691263{col 37}{space 1}   -2.25{col 46}{space 3}0.025{col 54}{space 4}-.2912353{col 67}{space 3}-.0199672
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1210996{col 26}{space 2}  .066105{col 37}{space 1}   -1.83{col 46}{space 3}0.067{col 54}{space 4}-.2508054{col 67}{space 3} .0086062
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.129868{col 26}{space 2} .0669367{col 37}{space 1}   -1.94{col 46}{space 3}0.053{col 54}{space 4}-.2612058{col 67}{space 3} .0014699
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .1211392{col 26}{space 2} .0689077{col 37}{space 1}    1.76{col 46}{space 3}0.079{col 54}{space 4}-.0140659{col 67}{space 3} .2563442
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3090577{col 26}{space 2}  .069253{col 37}{space 1}   -4.46{col 46}{space 3}0.000{col 54}{space 4}-.4449402{col 67}{space 3}-.1731751
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2464824{col 26}{space 2}  .070137{col 37}{space 1}   -3.51{col 46}{space 3}0.000{col 54}{space 4}-.3840997{col 67}{space 3}-.1088652
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0677103{col 26}{space 2} .0682526{col 37}{space 1}   -0.99{col 46}{space 3}0.321{col 54}{space 4}  -.20163{col 67}{space 3} .0662093
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1120025{col 26}{space 2} .0663659{col 37}{space 1}   -1.69{col 46}{space 3}0.092{col 54}{space 4}-.2422203{col 67}{space 3} .0182153
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  3.87352{col 26}{space 2} .0996898{col 37}{space 1}   38.86{col 46}{space 3}0.000{col 54}{space 4} 3.677917{col 67}{space 3} 4.069124
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        1{col 27}{space 1}        0{col 39}{result}{space 1}        1{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     2,206
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5131368 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4868632 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4984879 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5015121 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5296129 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4703871 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5053737 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4946263 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5200378 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4799622 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 4}.503441 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 4}.496559 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 4}.485762 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 4}.514238 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5007518 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4992482 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.450153{col 26}{space 2} .0548082{col 37}{space 1}   62.95{col 46}{space 3}0.000{col 54}{space 4} 3.342731{col 67}{space 3} 3.557575
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.294551{col 26}{space 2} .0462291{col 37}{space 1}   71.27{col 46}{space 3}0.000{col 54}{space 4} 3.203944{col 67}{space 3} 3.385159
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.435129{col 26}{space 2} .0506581{col 37}{space 1}   67.81{col 46}{space 3}0.000{col 54}{space 4} 3.335841{col 67}{space 3} 3.534417
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.314029{col 26}{space 2} .0489433{col 37}{space 1}   67.71{col 46}{space 3}0.000{col 54}{space 4} 3.218102{col 67}{space 3} 3.409957
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.435484{col 26}{space 2} .0516361{col 37}{space 1}   66.53{col 46}{space 3}0.000{col 54}{space 4} 3.334279{col 67}{space 3} 3.536689
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.305616{col 26}{space 2} .0481871{col 37}{space 1}   68.60{col 46}{space 3}0.000{col 54}{space 4} 3.211171{col 67}{space 3} 3.400061
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.522732{col 26}{space 2} .0465465{col 37}{space 1}   75.68{col 46}{space 3}0.000{col 54}{space 4} 3.431503{col 67}{space 3} 3.613962
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.213674{col 26}{space 2} .0551251{col 37}{space 1}   58.30{col 46}{space 3}0.000{col 54}{space 4} 3.105631{col 67}{space 3} 3.321718
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.496789{col 26}{space 2} .0515652{col 37}{space 1}   67.81{col 46}{space 3}0.000{col 54}{space 4} 3.395723{col 67}{space 3} 3.597855
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.250307{col 26}{space 2} .0507564{col 37}{space 1}   64.04{col 46}{space 3}0.000{col 54}{space 4} 3.150826{col 67}{space 3} 3.349787
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.314477{col 26}{space 2} .0498525{col 37}{space 1}   66.49{col 46}{space 3}0.000{col 54}{space 4} 3.216768{col 67}{space 3} 3.412186
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.435617{col 26}{space 2} .0516411{col 37}{space 1}   66.53{col 46}{space 3}0.000{col 54}{space 4} 3.334402{col 67}{space 3} 3.536831
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.409215{col 26}{space 2} .0493294{col 37}{space 1}   69.11{col 46}{space 3}0.000{col 54}{space 4} 3.312532{col 67}{space 3} 3.505899
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.341505{col 26}{space 2} .0516105{col 37}{space 1}   64.74{col 46}{space 3}0.000{col 54}{space 4}  3.24035{col 67}{space 3}  3.44266
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.430313{col 26}{space 2} .0472174{col 37}{space 1}   72.65{col 46}{space 3}0.000{col 54}{space 4} 3.337769{col 67}{space 3} 3.522857
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.318311{col 26}{space 2} .0524383{col 37}{space 1}   63.28{col 46}{space 3}0.000{col 54}{space 4} 3.215533{col 67}{space 3} 3.421088
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_argentina
{txt}
{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] if qcountry==3, absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,002
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   1000{txt}){col 67}= {res}      4.26
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0183
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0143
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0183
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     1,001{txt}{col 51}Root MSE{col 67}= {res}    1.5807

{txt}{ralign 78:(Std. Err. adjusted for {res:1,001} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3069017{col 26}{space 2} .0727293{col 37}{space 1}   -4.22{col 46}{space 3}0.000{col 54}{space 4}-.4496213{col 67}{space 3}-.1641822
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0259224{col 26}{space 2} .0732986{col 37}{space 1}    0.35{col 46}{space 3}0.724{col 54}{space 4}-.1179144{col 67}{space 3} .1697592
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1279082{col 26}{space 2} .0721005{col 37}{space 1}   -1.77{col 46}{space 3}0.076{col 54}{space 4}-.2693939{col 67}{space 3} .0135775
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0046879{col 26}{space 2} .0727727{col 37}{space 1}   -0.06{col 46}{space 3}0.949{col 54}{space 4}-.1474926{col 67}{space 3} .1381167
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2309728{col 26}{space 2} .0756658{col 37}{space 1}   -3.05{col 46}{space 3}0.002{col 54}{space 4}-.3794546{col 67}{space 3}-.0824909
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0578878{col 26}{space 2} .0711536{col 37}{space 1}   -0.81{col 46}{space 3}0.416{col 54}{space 4}-.1975152{col 67}{space 3} .0817397
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0974549{col 26}{space 2} .0705837{col 37}{space 1}   -1.38{col 46}{space 3}0.168{col 54}{space 4} -.235964{col 67}{space 3} .0410542
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0719312{col 26}{space 2} .0719882{col 37}{space 1}   -1.00{col 46}{space 3}0.318{col 54}{space 4}-.2131963{col 67}{space 3}  .069334
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.823676{col 26}{space 2} .1130583{col 37}{space 1}   33.82{col 46}{space 3}0.000{col 54}{space 4} 3.601817{col 67}{space 3} 4.045534
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        1{col 27}{space 1}        0{col 39}{result}{space 1}        1{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     2,002
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5018318 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4981682 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 5}.48845 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 5}.51155 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5003823 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4996177 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.4918617 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.5081383 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5178609 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4821391 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5138921 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4861079 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4881804 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5118196 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5039738 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4960262 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.545589{col 26}{space 2} .0544224{col 37}{space 1}   65.15{col 46}{space 3}0.000{col 54}{space 4} 3.438923{col 67}{space 3} 3.652255
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.238687{col 26}{space 2} .0520021{col 37}{space 1}   62.28{col 46}{space 3}0.000{col 54}{space 4} 3.136765{col 67}{space 3}  3.34061
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.37944{col 26}{space 2} .0543653{col 37}{space 1}   62.16{col 46}{space 3}0.000{col 54}{space 4} 3.272886{col 67}{space 3} 3.485994
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.405362{col 26}{space 2}  .052499{col 37}{space 1}   64.87{col 46}{space 3}0.000{col 54}{space 4} 3.302466{col 67}{space 3} 3.508258
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.456606{col 26}{space 2} .0529982{col 37}{space 1}   65.22{col 46}{space 3}0.000{col 54}{space 4} 3.352731{col 67}{space 3}  3.56048
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.328697{col 26}{space 2} .0530344{col 37}{space 1}   62.76{col 46}{space 3}0.000{col 54}{space 4} 3.224752{col 67}{space 3} 3.432643
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.504061{col 26}{space 2} .0547415{col 37}{space 1}   64.01{col 46}{space 3}0.000{col 54}{space 4}  3.39677{col 67}{space 3} 3.611353
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.273089{col 26}{space 2} .0536697{col 37}{space 1}   60.99{col 46}{space 3}0.000{col 54}{space 4} 3.167898{col 67}{space 3} 3.378279
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.42084{col 26}{space 2} .0549749{col 37}{space 1}   62.23{col 46}{space 3}0.000{col 54}{space 4} 3.313091{col 67}{space 3} 3.528589
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.362952{col 26}{space 2} .0501533{col 37}{space 1}   67.05{col 46}{space 3}0.000{col 54}{space 4} 3.264654{col 67}{space 3} 3.461251
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.395083{col 26}{space 2} .0526625{col 37}{space 1}   64.47{col 46}{space 3}0.000{col 54}{space 4} 3.291866{col 67}{space 3} 3.498299
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.390395{col 26}{space 2} .0537972{col 37}{space 1}   63.02{col 46}{space 3}0.000{col 54}{space 4} 3.284954{col 67}{space 3} 3.495835
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.44258{col 26}{space 2} .0519947{col 37}{space 1}   66.21{col 46}{space 3}0.000{col 54}{space 4} 3.340672{col 67}{space 3} 3.544487
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.345125{col 26}{space 2} .0529715{col 37}{space 1}   63.15{col 46}{space 3}0.000{col 54}{space 4} 3.241303{col 67}{space 3} 3.448947
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.42838{col 26}{space 2}  .054315{col 37}{space 1}   63.12{col 46}{space 3}0.000{col 54}{space 4} 3.321925{col 67}{space 3} 3.534836
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.356449{col 26}{space 2} .0515828{col 37}{space 1}   65.07{col 46}{space 3}0.000{col 54}{space 4} 3.255349{col 67}{space 3} 3.457549
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_pakistan
{txt}
{com}. 
. coefplot support_argentina support_kenya support_pakistan, xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. *Figure A25: Argentina and Kenya
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ  [pw = weight] if qcountry==1 | qcountry==2, absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,284
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   1641{txt}){col 67}= {res}     14.92
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0639
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0614
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0401
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     1,642{txt}{col 51}Root MSE{col 67}= {res}    1.4934

{txt}{ralign 78:(Std. Err. adjusted for {res:1,642} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1862314{col 26}{space 2} .0560755{col 37}{space 1}   -3.32{col 46}{space 3}0.001{col 54}{space 4}-.2962185{col 67}{space 3}-.0762443
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1146613{col 26}{space 2} .0543772{col 37}{space 1}   -2.11{col 46}{space 3}0.035{col 54}{space 4}-.2213173{col 67}{space 3}-.0080053
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1872461{col 26}{space 2} .0546842{col 37}{space 1}   -3.42{col 46}{space 3}0.001{col 54}{space 4}-.2945043{col 67}{space 3}-.0799879
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0689049{col 26}{space 2} .0564256{col 37}{space 1}    1.22{col 46}{space 3}0.222{col 54}{space 4}-.0417688{col 67}{space 3} .1795787
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.4069205{col 26}{space 2}  .056334{col 37}{space 1}   -7.22{col 46}{space 3}0.000{col 54}{space 4}-.5174146{col 67}{space 3}-.2964264
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2332041{col 26}{space 2}  .056755{col 37}{space 1}   -4.11{col 46}{space 3}0.000{col 54}{space 4} -.344524{col 67}{space 3}-.1218842
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1950167{col 26}{space 2} .0559889{col 37}{space 1}   -3.48{col 46}{space 3}0.001{col 54}{space 4}-.3048338{col 67}{space 3}-.0851995
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1686218{col 26}{space 2} .0544912{col 37}{space 1}   -3.09{col 46}{space 3}0.002{col 54}{space 4}-.2755013{col 67}{space 3}-.0617423
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.246527{col 26}{space 2} .0816055{col 37}{space 1}   52.04{col 46}{space 3}0.000{col 54}{space 4} 4.086465{col 67}{space 3} 4.406589
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        2{col 27}{space 1}        0{col 39}{result}{space 1}        2{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     3,284
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5048059 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4951941 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.5020617 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.4979383 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5197178 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4802822 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5096247 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4903753 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5165699 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4834301 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5023971 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4976029 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4853672 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5146328 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5024437 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4975563 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.63627{col 26}{space 2}  .042626{col 37}{space 1}   85.31{col 46}{space 3}0.000{col 54}{space 4} 3.552724{col 67}{space 3} 3.719815
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.450038{col 26}{space 2} .0375153{col 37}{space 1}   91.96{col 46}{space 3}0.000{col 54}{space 4}  3.37651{col 67}{space 3} 3.523567
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.601143{col 26}{space 2} .0398601{col 37}{space 1}   90.34{col 46}{space 3}0.000{col 54}{space 4} 3.523019{col 67}{space 3} 3.679268
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.486482{col 26}{space 2} .0393145{col 37}{space 1}   88.68{col 46}{space 3}0.000{col 54}{space 4} 3.409427{col 67}{space 3} 3.563537
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.63398{col 26}{space 2}  .040325{col 37}{space 1}   90.12{col 46}{space 3}0.000{col 54}{space 4} 3.554945{col 67}{space 3} 3.713016
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.446734{col 26}{space 2}  .038971{col 37}{space 1}   88.44{col 46}{space 3}0.000{col 54}{space 4} 3.370352{col 67}{space 3} 3.523116
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.740767{col 26}{space 2} .0376476{col 37}{space 1}   99.36{col 46}{space 3}0.000{col 54}{space 4} 3.666979{col 67}{space 3} 3.814555
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.333846{col 26}{space 2}   .04287{col 37}{space 1}   77.77{col 46}{space 3}0.000{col 54}{space 4} 3.249823{col 67}{space 3}  3.41787
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.660092{col 26}{space 2} .0400621{col 37}{space 1}   91.36{col 46}{space 3}0.000{col 54}{space 4} 3.581572{col 67}{space 3} 3.738613
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.426888{col 26}{space 2} .0407682{col 37}{space 1}   84.06{col 46}{space 3}0.000{col 54}{space 4} 3.346984{col 67}{space 3} 3.506792
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.51026{col 26}{space 2} .0397651{col 37}{space 1}   88.27{col 46}{space 3}0.000{col 54}{space 4} 3.432322{col 67}{space 3} 3.588198
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.579165{col 26}{space 2} .0408406{col 37}{space 1}   87.64{col 46}{space 3}0.000{col 54}{space 4} 3.499119{col 67}{space 3} 3.659211
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.644411{col 26}{space 2}  .039298{col 37}{space 1}   92.74{col 46}{space 3}0.000{col 54}{space 4} 3.567388{col 67}{space 3} 3.721434
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.449394{col 26}{space 2}  .040916{col 37}{space 1}   84.30{col 46}{space 3}0.000{col 54}{space 4} 3.369201{col 67}{space 3} 3.529588
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.627948{col 26}{space 2} .0385389{col 37}{space 1}   94.14{col 46}{space 3}0.000{col 54}{space 4} 3.552413{col 67}{space 3} 3.703483
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.459326{col 26}{space 2} .0406991{col 37}{space 1}   85.00{col 46}{space 3}0.000{col 54}{space 4} 3.379557{col 67}{space 3} 3.539095
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo country1
{txt}
{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ  [pw = weight] if qcountry==1 | qcountry==3, absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,080
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   1539{txt}){col 67}= {res}     12.00
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0550
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0522
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0336
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     1,540{txt}{col 51}Root MSE{col 67}= {res}    1.5558

{txt}{ralign 78:(Std. Err. adjusted for {res:1,540} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.291975{col 26}{space 2} .0578561{col 37}{space 1}   -5.05{col 46}{space 3}0.000{col 54}{space 4}-.4054601{col 67}{space 3}-.1784898
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0180269{col 26}{space 2}  .058448{col 37}{space 1}   -0.31{col 46}{space 3}0.758{col 54}{space 4}-.1326731{col 67}{space 3} .0966193
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1935696{col 26}{space 2} .0575786{col 37}{space 1}   -3.36{col 46}{space 3}0.001{col 54}{space 4}-.3065104{col 67}{space 3}-.0806289
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0144745{col 26}{space 2}  .058594{col 37}{space 1}   -0.25{col 46}{space 3}0.805{col 54}{space 4} -.129407{col 67}{space 3}  .100458
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3612848{col 26}{space 2} .0597403{col 37}{space 1}   -6.05{col 46}{space 3}0.000{col 54}{space 4}-.4784658{col 67}{space 3}-.2441038
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1050223{col 26}{space 2} .0574774{col 37}{space 1}   -1.83{col 46}{space 3}0.068{col 54}{space 4}-.2177647{col 67}{space 3} .0077201
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2172386{col 26}{space 2} .0571771{col 37}{space 1}   -3.80{col 46}{space 3}0.000{col 54}{space 4}-.3293917{col 67}{space 3}-.1050854
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1394926{col 26}{space 2} .0572722{col 37}{space 1}   -2.44{col 46}{space 3}0.015{col 54}{space 4}-.2518324{col 67}{space 3}-.0271528
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.234521{col 26}{space 2} .0888731{col 37}{space 1}   47.65{col 46}{space 3}0.000{col 54}{space 4} 4.060196{col 67}{space 3} 4.408847
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        2{col 27}{space 1}        0{col 39}{result}{space 1}        2{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     3,080
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.4969058 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.5030942 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4957738 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5042262 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5000625 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4999375 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5011234 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4988766 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5149251 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4850749 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5091211 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4908789 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 4}.486913 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 4}.513087 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 5}.50465 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 5}.49535 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.714075{col 26}{space 2} .0419786{col 37}{space 1}   88.48{col 46}{space 3}0.000{col 54}{space 4} 3.631798{col 67}{space 3} 3.796351
{txt}{space 9}No  {c |}{col 14}{res}{space 2}   3.4221{col 26}{space 2} .0405493{col 37}{space 1}   84.39{col 46}{space 3}0.000{col 54}{space 4} 3.342625{col 67}{space 3} 3.501575
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.576273{col 26}{space 2} .0417495{col 37}{space 1}   85.66{col 46}{space 3}0.000{col 54}{space 4} 3.494446{col 67}{space 3} 3.658101
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.558247{col 26}{space 2}    .0412{col 37}{space 1}   86.37{col 46}{space 3}0.000{col 54}{space 4} 3.477496{col 67}{space 3} 3.638997
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.663956{col 26}{space 2} .0406705{col 37}{space 1}   90.09{col 46}{space 3}0.000{col 54}{space 4} 3.584244{col 67}{space 3} 3.743669
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.470387{col 26}{space 2} .0416615{col 37}{space 1}   83.30{col 46}{space 3}0.000{col 54}{space 4} 3.388732{col 67}{space 3} 3.552042
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.742434{col 26}{space 2} .0419879{col 37}{space 1}   89.13{col 46}{space 3}0.000{col 54}{space 4} 3.660139{col 67}{space 3} 3.824729
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.381149{col 26}{space 2} .0418528{col 37}{space 1}   80.79{col 46}{space 3}0.000{col 54}{space 4} 3.299119{col 67}{space 3} 3.463179
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.618737{col 26}{space 2} .0418218{col 37}{space 1}   86.53{col 46}{space 3}0.000{col 54}{space 4} 3.536768{col 67}{space 3} 3.700706
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.513715{col 26}{space 2} .0404005{col 37}{space 1}   86.97{col 46}{space 3}0.000{col 54}{space 4} 3.434531{col 67}{space 3} 3.592898
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.574405{col 26}{space 2} .0411612{col 37}{space 1}   86.84{col 46}{space 3}0.000{col 54}{space 4}  3.49373{col 67}{space 3} 3.655079
{txt}{space 9}No  {c |}{col 14}{res}{space 2}  3.55993{col 26}{space 2} .0418883{col 37}{space 1}   84.99{col 46}{space 3}0.000{col 54}{space 4} 3.477831{col 67}{space 3}  3.64203
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.678646{col 26}{space 2} .0404253{col 37}{space 1}   91.00{col 46}{space 3}0.000{col 54}{space 4} 3.599414{col 67}{space 3} 3.757878
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.461408{col 26}{space 2} .0415803{col 37}{space 1}   83.25{col 46}{space 3}0.000{col 54}{space 4} 3.379912{col 67}{space 3} 3.542903
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.636281{col 26}{space 2} .0421489{col 37}{space 1}   86.27{col 46}{space 3}0.000{col 54}{space 4} 3.553671{col 67}{space 3} 3.718892
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.496789{col 26}{space 2} .0399224{col 37}{space 1}   87.59{col 46}{space 3}0.000{col 54}{space 4} 3.418542{col 67}{space 3} 3.575035
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo country2
{txt}
{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ  [pw = weight] if qcountry==2 | qcountry==3, absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     4,208
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2103{txt}){col 67}= {res}      9.59
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0198
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0177
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0197
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,104{txt}{col 51}Root MSE{col 67}= {res}    1.5328

{txt}{ralign 78:(Std. Err. adjusted for {res:2,104} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2228679{col 26}{space 2} .0500293{col 37}{space 1}   -4.45{col 46}{space 3}0.000{col 54}{space 4}  -.32098{col 67}{space 3}-.1247557
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0488404{col 26}{space 2} .0491079{col 37}{space 1}   -0.99{col 46}{space 3}0.320{col 54}{space 4}-.1451457{col 67}{space 3} .0474648
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1292554{col 26}{space 2} .0490788{col 37}{space 1}   -2.63{col 46}{space 3}0.009{col 54}{space 4}-.2255034{col 67}{space 3}-.0330074
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0587113{col 26}{space 2}  .049987{col 37}{space 1}    1.17{col 46}{space 3}0.240{col 54}{space 4}-.0393178{col 67}{space 3} .1567404
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2727916{col 26}{space 2} .0511958{col 37}{space 1}   -5.33{col 46}{space 3}0.000{col 54}{space 4}-.3731912{col 67}{space 3} -.172392
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1602705{col 26}{space 2} .0499195{col 37}{space 1}   -3.21{col 46}{space 3}0.001{col 54}{space 4}-.2581673{col 67}{space 3}-.0623737
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0778325{col 26}{space 2} .0490069{col 37}{space 1}   -1.59{col 46}{space 3}0.112{col 54}{space 4}-.1739396{col 67}{space 3} .0182746
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.090769{col 26}{space 2} .0488557{col 37}{space 1}   -1.86{col 46}{space 3}0.063{col 54}{space 4}-.1865796{col 67}{space 3} .0050415
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.845828{col 26}{space 2} .0750584{col 37}{space 1}   51.24{col 46}{space 3}0.000{col 54}{space 4} 3.698631{col 67}{space 3} 3.993024
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        2{col 27}{space 1}        0{col 39}{result}{space 1}        2{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     4,208
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5077583 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4922417 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4937123 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5062877 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5157062 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4842938 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.4989452 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.5010548 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5190021 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4809979 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5084132 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4915868 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4869126 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5130874 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5022847 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4977153 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.492809{col 26}{space 2} .0387197{col 37}{space 1}   90.21{col 46}{space 3}0.000{col 54}{space 4}  3.41692{col 67}{space 3} 3.568699
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.269942{col 26}{space 2}  .034593{col 37}{space 1}   94.53{col 46}{space 3}0.000{col 54}{space 4} 3.202141{col 67}{space 3} 3.337743
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.407832{col 26}{space 2} .0370713{col 37}{space 1}   91.93{col 46}{space 3}0.000{col 54}{space 4} 3.335173{col 67}{space 3}  3.48049
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.358991{col 26}{space 2} .0358036{col 37}{space 1}   93.82{col 46}{space 3}0.000{col 54}{space 4} 3.288818{col 67}{space 3} 3.429165
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.445702{col 26}{space 2} .0370611{col 37}{space 1}   92.97{col 46}{space 3}0.000{col 54}{space 4} 3.373064{col 67}{space 3} 3.518341
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.316447{col 26}{space 2} .0357212{col 37}{space 1}   92.84{col 46}{space 3}0.000{col 54}{space 4} 3.246435{col 67}{space 3} 3.386459
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.514317{col 26}{space 2} .0357024{col 37}{space 1}   98.43{col 46}{space 3}0.000{col 54}{space 4} 3.444341{col 67}{space 3} 3.584292
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.241525{col 26}{space 2} .0386214{col 37}{space 1}   83.93{col 46}{space 3}0.000{col 54}{space 4} 3.165829{col 67}{space 3} 3.317222
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.461891{col 26}{space 2} .0375628{col 37}{space 1}   92.16{col 46}{space 3}0.000{col 54}{space 4}  3.38827{col 67}{space 3} 3.535513
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.301621{col 26}{space 2} .0358037{col 37}{space 1}   92.21{col 46}{space 3}0.000{col 54}{space 4} 3.231447{col 67}{space 3} 3.371795
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.353687{col 26}{space 2} .0362324{col 37}{space 1}   92.56{col 46}{space 3}0.000{col 54}{space 4} 3.282673{col 67}{space 3} 3.424701
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.412398{col 26}{space 2} .0372266{col 37}{space 1}   91.67{col 46}{space 3}0.000{col 54}{space 4} 3.339436{col 67}{space 3} 3.485361
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.423039{col 26}{space 2} .0358416{col 37}{space 1}   95.50{col 46}{space 3}0.000{col 54}{space 4} 3.352791{col 67}{space 3} 3.493288
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.345207{col 26}{space 2} .0369156{col 37}{space 1}   90.62{col 46}{space 3}0.000{col 54}{space 4} 3.272854{col 67}{space 3}  3.41756
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.428282{col 26}{space 2} .0358829{col 37}{space 1}   95.54{col 46}{space 3}0.000{col 54}{space 4} 3.357953{col 67}{space 3} 3.498611
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.337513{col 26}{space 2} .0368179{col 37}{space 1}   90.65{col 46}{space 3}0.000{col 54}{space 4} 3.265351{col 67}{space 3} 3.409675
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo country3
{txt}
{com}. 
. coefplot country1  , xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. *Figure A26: Argentina and Pakistan
. coefplot country3  , xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. *Figure A27: Kenya and Pakistan
. coefplot country2  , xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. *Figure A28: Controlling for individual-level covariates
. foreach x of varlist DEM4_Ken DEM5_Ken LOC_TYPE_Ken income_Ken region_Ken education_Ar GeoPC_Region1_Ar income_Ar empl_stat_Ar employment_Pak income_Pak natgroup_Pak maritalstatus_Pak education_Pak region_Pak{c -(}
{txt}  2{com}. gen nm`x'=`x' 
{txt}  3{com}. replace nm`x'=999 if nm`x'==.
{txt}  4{com}. {c )-}
{txt}(4,208 missing values generated)
(4,208 real changes made)
(4,208 missing values generated)
(4,208 real changes made)
(4,210 missing values generated)
(4,210 real changes made)
(4,208 missing values generated)
(4,208 real changes made)
(4,208 missing values generated)
(4,208 real changes made)
(3,080 missing values generated)
(3,080 real changes made)
(3,080 missing values generated)
(3,080 real changes made)
(3,080 missing values generated)
(3,080 real changes made)
(3,080 missing values generated)
(3,080 real changes made)
(3,284 missing values generated)
(3,284 real changes made)
(3,296 missing values generated)
(3,296 real changes made)
(3,284 missing values generated)
(3,284 real changes made)
(3,284 missing values generated)
(3,284 real changes made)
(3,326 missing values generated)
(3,326 real changes made)
(3,316 missing values generated)
(3,316 real changes made)

{com}. 
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ [pw = weight] , absorb(qcountry nm*) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 18 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 16 HDFE groups{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}     17.65
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0765
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0527
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0287
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5207

{txt}{ralign 78:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2} -.226335{col 26}{space 2} .0438132{col 37}{space 1}   -5.17{col 46}{space 3}0.000{col 54}{space 4}-.3122467{col 67}{space 3}-.1404234
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0563592{col 26}{space 2} .0441295{col 37}{space 1}   -1.28{col 46}{space 3}0.202{col 54}{space 4}-.1428911{col 67}{space 3} .0301728
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1663946{col 26}{space 2} .0434577{col 37}{space 1}   -3.83{col 46}{space 3}0.000{col 54}{space 4}-.2516091{col 67}{space 3}-.0811801
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0166946{col 26}{space 2} .0445401{col 37}{space 1}    0.37{col 46}{space 3}0.708{col 54}{space 4}-.0706425{col 67}{space 3} .1040316
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3471605{col 26}{space 2} .0448432{col 37}{space 1}   -7.74{col 46}{space 3}0.000{col 54}{space 4}-.4350918{col 67}{space 3}-.2592292
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1623182{col 26}{space 2} .0444978{col 37}{space 1}   -3.65{col 46}{space 3}0.000{col 54}{space 4}-.2495722{col 67}{space 3}-.0750642
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1603063{col 26}{space 2} .0435289{col 37}{space 1}   -3.68{col 46}{space 3}0.000{col 54}{space 4}-.2456604{col 67}{space 3}-.0749522
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1281998{col 26}{space 2} .0428689{col 37}{space 1}   -2.99{col 46}{space 3}0.003{col 54}{space 4}-.2122599{col 67}{space 3}-.0441397
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.094014{col 26}{space 2} .0661341{col 37}{space 1}   61.90{col 46}{space 3}0.000{col 54}{space 4} 3.964335{col 67}{space 3} 4.223694
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 21}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}         Absorbed FE{col 22}{c |} Categories{col 35} - Redundant{col 47}  = Num. Coefs{col 62}{c |}
{res}{col 1}{text}{hline 21}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}            qcountry{col 22}{c |}{space 1}        3{col 35}{space 1}        0{col 47}{result}{space 1}        3{col 61}{text} {col 62}{c |}
{res}{col 1}{text}          nmDEM4_Ken{col 22}{c |}{space 1}       11{col 35}{space 1}        2{col 47}{result}{space 1}        9{col 61}{text} {col 62}{c |}
{res}{col 1}{text}          nmDEM5_Ken{col 22}{c |}{space 1}        4{col 35}{space 1}        4{col 47}{result}{space 1}        0{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}      nmLOC_TYPE_Ken{col 22}{c |}{space 1}        5{col 35}{space 1}        1{col 47}{result}{space 1}        4{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}        nmincome_Ken{col 22}{c |}{space 1}        7{col 35}{space 1}        2{col 47}{result}{space 1}        5{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}        nmregion_Ken{col 22}{c |}{space 1}        9{col 35}{space 1}        2{col 47}{result}{space 1}        7{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}      nmeducation_Ar{col 22}{c |}{space 1}       11{col 35}{space 1}        2{col 47}{result}{space 1}        9{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}  nmGeoPC_Region1_Ar{col 22}{c |}{space 1}       25{col 35}{space 1}        2{col 47}{result}{space 1}       23{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}         nmincome_Ar{col 22}{c |}{space 1}       14{col 35}{space 1}        2{col 47}{result}{space 1}       12{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}      nmempl_stat_Ar{col 22}{c |}{space 1}       11{col 35}{space 1}        2{col 47}{result}{space 1}        9{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}    nmemployment_Pak{col 22}{c |}{space 1}        9{col 35}{space 1}        2{col 47}{result}{space 1}        7{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}        nmincome_Pak{col 22}{c |}{space 1}       17{col 35}{space 1}        1{col 47}{result}{space 1}       16{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}      nmnatgroup_Pak{col 22}{c |}{space 1}        7{col 35}{space 1}        2{col 47}{result}{space 1}        5{col 61}{text}?{col 62}{c |}
{res}{col 1}{text} nmmaritalstatus_Pak{col 22}{c |}{space 1}        6{col 35}{space 1}        2{col 47}{result}{space 1}        4{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}     nmeducation_Pak{col 22}{c |}{space 1}        8{col 35}{space 1}        1{col 47}{result}{space 1}        7{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}        nmregion_Pak{col 22}{c |}{space 1}        7{col 35}{space 1}        1{col 47}{result}{space 1}        6{col 61}{text}?{col 62}{c |}
{res}{col 1}{text}{hline 21}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     5,286
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5036795 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4963205 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4969065 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5030935 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5123948 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4876052 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5028972 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4971028 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5170588 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4829412 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 3}.5067507 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 3}.4932493 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4864326 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5135674 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5030232 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4969768 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.599063{col 26}{space 2} .0324403{col 37}{space 1}  110.94{col 46}{space 3}0.000{col 54}{space 4} 3.535481{col 67}{space 3} 3.662644
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.372728{col 26}{space 2} .0301723{col 37}{space 1}  111.78{col 46}{space 3}0.000{col 54}{space 4} 3.313591{col 67}{space 3} 3.431864
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.515082{col 26}{space 2} .0317667{col 37}{space 1}  110.65{col 46}{space 3}0.000{col 54}{space 4}  3.45282{col 67}{space 3} 3.577343
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.458723{col 26}{space 2} .0311261{col 37}{space 1}  111.12{col 46}{space 3}0.000{col 54}{space 4} 3.397717{col 67}{space 3} 3.519729
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.567863{col 26}{space 2} .0314558{col 37}{space 1}  113.42{col 46}{space 3}0.000{col 54}{space 4} 3.506211{col 67}{space 3} 3.629515
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.401468{col 26}{space 2} .0309432{col 37}{space 1}  109.93{col 46}{space 3}0.000{col 54}{space 4} 3.340821{col 67}{space 3} 3.462116
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.654386{col 26}{space 2} .0310018{col 37}{space 1}  117.88{col 46}{space 3}0.000{col 54}{space 4} 3.593624{col 67}{space 3} 3.715148
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.307226{col 26}{space 2} .0324076{col 37}{space 1}  102.05{col 46}{space 3}0.000{col 54}{space 4} 3.243708{col 67}{space 3} 3.370743
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.566791{col 26}{space 2} .0316988{col 37}{space 1}  112.52{col 46}{space 3}0.000{col 54}{space 4} 3.504663{col 67}{space 3}  3.62892
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.404473{col 26}{space 2}  .031446{col 37}{space 1}  108.26{col 46}{space 3}0.000{col 54}{space 4}  3.34284{col 67}{space 3} 3.466106
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.478429{col 26}{space 2} .0314515{col 37}{space 1}  110.60{col 46}{space 3}0.000{col 54}{space 4} 3.416785{col 67}{space 3} 3.540073
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.495124{col 26}{space 2} .0317305{col 37}{space 1}  110.15{col 46}{space 3}0.000{col 54}{space 4} 3.432933{col 67}{space 3} 3.557314
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.569056{col 26}{space 2} .0312223{col 37}{space 1}  114.31{col 46}{space 3}0.000{col 54}{space 4} 3.507861{col 67}{space 3} 3.630251
{txt}{space 9}No  {c |}{col 14}{res}{space 2}  3.40875{col 26}{space 2} .0312388{col 37}{space 1}  109.12{col 46}{space 3}0.000{col 54}{space 4} 3.347523{col 67}{space 3} 3.469977
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.55044{col 26}{space 2} .0309169{col 37}{space 1}  114.84{col 46}{space 3}0.000{col 54}{space 4} 3.489844{col 67}{space 3} 3.611036
{txt}{space 9}No  {c |}{col 14}{res}{space 2}  3.42224{col 26}{space 2} .0310981{col 37}{space 1}  110.05{col 46}{space 3}0.000{col 54}{space 4} 3.361289{col 67}{space 3} 3.483192
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_controls
{txt}
{com}. 
. coefplot support_controls , xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. *Figure A29: Estimates without probability weights
. reghdfe support i.invest i.tariff i.debt i.privatize i.corrupt i.poverty i.climate i.genderequ , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}     17.96
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0431
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0413
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0281
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5295

{txt}{ralign 78:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}     support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.2049001{col 26}{space 2} .0421752{col 37}{space 1}   -4.86{col 46}{space 3}0.000{col 54}{space 4}-.2875998{col 67}{space 3}-.1222004
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.0763932{col 26}{space 2} .0424235{col 37}{space 1}   -1.80{col 46}{space 3}0.072{col 54}{space 4}-.1595799{col 67}{space 3} .0067934
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1691232{col 26}{space 2} .0425652{col 37}{space 1}   -3.97{col 46}{space 3}0.000{col 54}{space 4}-.2525876{col 67}{space 3}-.0856587
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 9}No  {c |}{col 14}{res}{space 2} .0258455{col 26}{space 2} .0431669{col 37}{space 1}    0.60{col 46}{space 3}0.549{col 54}{space 4}-.0587989{col 67}{space 3} .1104899
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.3492538{col 26}{space 2} .0433667{col 37}{space 1}   -8.05{col 46}{space 3}0.000{col 54}{space 4}-.4342899{col 67}{space 3}-.2642178
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1739657{col 26}{space 2} .0427834{col 37}{space 1}   -4.07{col 46}{space 3}0.000{col 54}{space 4} -.257858{col 67}{space 3}-.0900734
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1632246{col 26}{space 2} .0423029{col 37}{space 1}   -3.86{col 46}{space 3}0.000{col 54}{space 4}-.2461748{col 67}{space 3}-.0802743
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 9}No  {c |}{col 14}{res}{space 2}-.1094273{col 26}{space 2}  .041921{col 37}{space 1}   -2.61{col 46}{space 3}0.009{col 54}{space 4}-.1916285{col 67}{space 3}-.0272261
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.089704{col 26}{space 2} .0648727{col 37}{space 1}   63.04{col 46}{space 3}0.000{col 54}{space 4} 3.962497{col 67}{space 3} 4.216911
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. margins invest tariff debt corrupt poverty privatize climate genderequ , atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}     5,286
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:1.invest}{space 8}{txt:=} {space 3}.5013243 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.invest}{space 8}{txt:=} {space 3}.4986757 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.tariff}{space 8}{txt:=} {space 3}.4948922 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.tariff}{space 8}{txt:=} {space 3}.5051078 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.debt}{space 10}{txt:=} {space 3}.5081347 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.debt}{space 10}{txt:=} {space 3}.4918653 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.privatize}{space 5}{txt:=} {space 3}.5026485 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.privatize}{space 5}{txt:=} {space 3}.4973515 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.corrupt}{space 7}{txt:=} {space 3}.5189179 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.corrupt}{space 7}{txt:=} {space 3}.4810821 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.poverty}{space 7}{txt:=} {space 4}.505297 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.poverty}{space 7}{txt:=} {space 4}.494703 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.climate}{space 7}{txt:=} {space 3}.4877034 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.climate}{space 7}{txt:=} {space 3}.5122966 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1.genderequ}{space 5}{txt:=} {space 3}.5017026 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.genderequ}{space 5}{txt:=} {space 3}.4982974 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}invest {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.588558{col 26}{space 2} .0312569{col 37}{space 1}  114.81{col 46}{space 3}0.000{col 54}{space 4} 3.527296{col 67}{space 3}  3.64982
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.383658{col 26}{space 2} .0301642{col 37}{space 1}  112.17{col 46}{space 3}0.000{col 54}{space 4} 3.324537{col 67}{space 3} 3.442779
{txt}{space 12} {c |}
{space 6}tariff {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.524966{col 26}{space 2} .0311164{col 37}{space 1}  113.28{col 46}{space 3}0.000{col 54}{space 4} 3.463979{col 67}{space 3} 3.585953
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.448573{col 26}{space 2} .0304899{col 37}{space 1}  113.11{col 46}{space 3}0.000{col 54}{space 4} 3.388814{col 67}{space 3} 3.508332
{txt}{space 12} {c |}
{space 8}debt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.569565{col 26}{space 2} .0307536{col 37}{space 1}  116.07{col 46}{space 3}0.000{col 54}{space 4} 3.509289{col 67}{space 3} 3.629841
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.400442{col 26}{space 2} .0309476{col 37}{space 1}  109.88{col 46}{space 3}0.000{col 54}{space 4} 3.339786{col 67}{space 3} 3.461098
{txt}{space 12} {c |}
{space 5}corrupt {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.654399{col 26}{space 2} .0305569{col 37}{space 1}  119.59{col 46}{space 3}0.000{col 54}{space 4} 3.594508{col 67}{space 3} 3.714289
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.305145{col 26}{space 2} .0317123{col 37}{space 1}  104.22{col 46}{space 3}0.000{col 54}{space 4}  3.24299{col 67}{space 3}   3.3673
{txt}{space 12} {c |}
{space 5}poverty {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2}  3.57244{col 26}{space 2}  .031167{col 37}{space 1}  114.62{col 46}{space 3}0.000{col 54}{space 4} 3.511354{col 67}{space 3} 3.633527
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.398475{col 26}{space 2} .0306771{col 37}{space 1}  110.78{col 46}{space 3}0.000{col 54}{space 4} 3.338349{col 67}{space 3} 3.458601
{txt}{space 12} {c |}
{space 3}privatize {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.473525{col 26}{space 2} .0309331{col 37}{space 1}  112.29{col 46}{space 3}0.000{col 54}{space 4} 3.412897{col 67}{space 3} 3.534153
{txt}{space 9}No  {c |}{col 14}{res}{space 2}  3.49937{col 26}{space 2} .0311862{col 37}{space 1}  112.21{col 46}{space 3}0.000{col 54}{space 4} 3.438247{col 67}{space 3} 3.560494
{txt}{space 12} {c |}
{space 5}climate {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.569999{col 26}{space 2} .0305974{col 37}{space 1}  116.68{col 46}{space 3}0.000{col 54}{space 4} 3.510029{col 67}{space 3} 3.629968
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.406774{col 26}{space 2}  .030907{col 37}{space 1}  110.23{col 46}{space 3}0.000{col 54}{space 4} 3.346197{col 67}{space 3} 3.467351
{txt}{space 12} {c |}
{space 3}genderequ {c |}
{space 8}Yes  {c |}{col 14}{res}{space 2} 3.540906{col 26}{space 2}  .030432{col 37}{space 1}  116.35{col 46}{space 3}0.000{col 54}{space 4} 3.481261{col 67}{space 3} 3.600552
{txt}{space 9}No  {c |}{col 14}{res}{space 2} 3.431479{col 26}{space 2} .0308274{col 37}{space 1}  111.31{col 46}{space 3}0.000{col 54}{space 4} 3.371058{col 67}{space 3}   3.4919
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo support_noweight
{txt}
{com}. 
. coefplot support_noweight , xtitle(Marginal Means) scheme(plotplainblind) xlabel(3(0.1)4) headings(1.invest = "{c -(}bf:Open up to foreign investors{c )-}" 1.tariff = "{c -(}bf:Reduce tariffs{c )-}" 1.debt = "{c -(}bf:Reduce debt{c )-}" 1.corrupt = "{c -(}bf:Fight corruption{c )-}" 1.poverty = "{c -(}bf:Introduce anti-poverty policies{c )-}" 1.privatize = "{c -(}bf:Privatize SOEs{c )-}" 1.climate = "{c -(}bf:Fight climate change{c )-}" 1.genderequ = "{c -(}bf:Improve gender equality{c )-}")
{res}{txt}
{com}. 
. *Table A30: Adjusting for multiple comparisons
. foreach x of varlist invest tariff debt corrupt poverty privatize climate genderequ{c -(}
{txt}  2{com}. gen zero_`x'=`x' 
{txt}  3{com}. replace zero_`x'=0 if zero_`x'==2
{txt}  4{com}. {c )-}
{txt}(2,636 real changes made)
(2,670 real changes made)
(2,600 real changes made)
(2,543 real changes made)
(2,615 real changes made)
(2,629 real changes made)
(2,708 real changes made)
(2,634 real changes made)

{com}. 
. label var zero_invest "Open up to foreign investors"
{txt}
{com}. label var zero_tariff "Reduce tariffs"
{txt}
{com}. label var zero_debt "Reduce debt"
{txt}
{com}. label var zero_corrupt "Fight corruption"
{txt}
{com}. label var zero_poverty "Introduce anti-poverty policies"
{txt}
{com}. label var zero_privatize "Privatize SOEs"
{txt}
{com}. label var zero_climate "Fight climate change"
{txt}
{com}. label var zero_genderequ "Improve gender equality"
{txt}
{com}. 
. 
. reghdfe support zero_invest zero_tariff zero_debt zero_privatize zero_corrupt zero_poverty zero_climate zero_genderequ [pw = weight] , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}     17.24
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0451
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0433
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0284
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5282

{txt}{ralign 80:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}       support{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}zero_invest {c |}{col 16}{res}{space 2} .2303392{col 28}{space 2} .0443747{col 39}{space 1}    5.19{col 48}{space 3}0.000{col 56}{space 4} .1433266{col 69}{space 3} .3173519
{txt}{space 3}zero_tariff {c |}{col 16}{res}{space 2} .0589854{col 28}{space 2} .0437678{col 39}{space 1}    1.35{col 48}{space 3}0.178{col 56}{space 4}-.0268371{col 69}{space 3}  .144808
{txt}{space 5}zero_debt {c |}{col 16}{res}{space 2} .1664032{col 28}{space 2} .0436616{col 39}{space 1}    3.81{col 48}{space 3}0.000{col 56}{space 4} .0807888{col 69}{space 3} .2520175
{txt}zero_privatize {c |}{col 16}{res}{space 2}-.0399676{col 28}{space 2} .0446187{col 39}{space 1}   -0.90{col 48}{space 3}0.370{col 56}{space 4}-.1274586{col 69}{space 3} .0475234
{txt}{space 2}zero_corrupt {c |}{col 16}{res}{space 2} .3411422{col 28}{space 2} .0453112{col 39}{space 1}    7.53{col 48}{space 3}0.000{col 56}{space 4} .2522931{col 69}{space 3} .4299913
{txt}{space 2}zero_poverty {c |}{col 16}{res}{space 2} .1674544{col 28}{space 2} .0444102{col 39}{space 1}    3.77{col 48}{space 3}0.000{col 56}{space 4}  .080372{col 69}{space 3} .2545368
{txt}{space 2}zero_climate {c |}{col 16}{res}{space 2} .1545761{col 28}{space 2} .0438521{col 39}{space 1}    3.52{col 48}{space 3}0.000{col 56}{space 4} .0685882{col 69}{space 3}  .240564
{txt}zero_genderequ {c |}{col 16}{res}{space 2} .1295466{col 28}{space 2} .0434812{col 39}{space 1}    2.98{col 48}{space 3}0.003{col 56}{space 4} .0442859{col 69}{space 3} .2148073
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 2.874632{col 28}{space 2} .0660967{col 39}{space 1}   43.49{col 48}{space 3}0.000{col 56}{space 4} 2.745025{col 69}{space 3} 3.004239
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. eststo support_amce
{txt}
{com}. 
. reghdfe cuts zero_invest zero_tariff zero_debt zero_privatize zero_corrupt zero_poverty zero_climate zero_genderequ [pw = weight] , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}     10.38
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0351
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0333
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0187
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5863

{txt}{ralign 80:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}          cuts{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}zero_invest {c |}{col 16}{res}{space 2} .1192542{col 28}{space 2} .0450769{col 39}{space 1}    2.65{col 48}{space 3}0.008{col 56}{space 4} .0308647{col 69}{space 3} .2076438
{txt}{space 3}zero_tariff {c |}{col 16}{res}{space 2} .0682027{col 28}{space 2} .0459075{col 39}{space 1}    1.49{col 48}{space 3}0.137{col 56}{space 4}-.0218156{col 69}{space 3} .1582209
{txt}{space 5}zero_debt {c |}{col 16}{res}{space 2} .2006735{col 28}{space 2} .0456124{col 39}{space 1}    4.40{col 48}{space 3}0.000{col 56}{space 4} .1112339{col 69}{space 3} .2901132
{txt}zero_privatize {c |}{col 16}{res}{space 2} .0389614{col 28}{space 2} .0459258{col 39}{space 1}    0.85{col 48}{space 3}0.396{col 56}{space 4}-.0510928{col 69}{space 3} .1290155
{txt}{space 2}zero_corrupt {c |}{col 16}{res}{space 2}  .241846{col 28}{space 2} .0477513{col 39}{space 1}    5.06{col 48}{space 3}0.000{col 56}{space 4} .1482123{col 69}{space 3} .3354798
{txt}{space 2}zero_poverty {c |}{col 16}{res}{space 2}   .18123{col 28}{space 2} .0454209{col 39}{space 1}    3.99{col 48}{space 3}0.000{col 56}{space 4} .0921659{col 69}{space 3} .2702941
{txt}{space 2}zero_climate {c |}{col 16}{res}{space 2} .1119305{col 28}{space 2} .0459902{col 39}{space 1}    2.43{col 48}{space 3}0.015{col 56}{space 4}   .02175{col 69}{space 3} .2021109
{txt}zero_genderequ {c |}{col 16}{res}{space 2} .1645639{col 28}{space 2} .0460117{col 39}{space 1}    3.58{col 48}{space 3}0.000{col 56}{space 4} .0743413{col 69}{space 3} .2547866
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 3.071404{col 28}{space 2} .0714676{col 39}{space 1}   42.98{col 48}{space 3}0.000{col 56}{space 4} 2.931266{col 69}{space 3} 3.211542
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. eststo cuts_amce
{txt}
{com}. 
. reghdfe taxes zero_invest zero_tariff zero_debt zero_privatize zero_corrupt zero_poverty zero_climate zero_genderequ [pw = weight] , absorb(qcountry) cluster(id)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     5,286
{txt}Absorbing 1 HDFE group{col 51}F({res}   8{txt},{res}   2642{txt}){col 67}= {res}      7.48
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0281
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0262
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0126
{txt}{col 1}Number of clusters ({res}id{txt}) {col 30}= {res}     2,643{txt}{col 51}Root MSE{col 67}= {res}    1.5697

{txt}{ralign 80:(Std. Err. adjusted for {res:2,643} clusters in id)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}         taxes{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}zero_invest {c |}{col 16}{res}{space 2}  .155126{col 28}{space 2} .0451633{col 39}{space 1}    3.43{col 48}{space 3}0.001{col 56}{space 4}  .066567{col 69}{space 3}  .243685
{txt}{space 3}zero_tariff {c |}{col 16}{res}{space 2} .0302376{col 28}{space 2} .0466195{col 39}{space 1}    0.65{col 48}{space 3}0.517{col 56}{space 4}-.0611769{col 69}{space 3}  .121652
{txt}{space 5}zero_debt {c |}{col 16}{res}{space 2} .1646791{col 28}{space 2} .0457554{col 39}{space 1}    3.60{col 48}{space 3}0.000{col 56}{space 4} .0749589{col 69}{space 3} .2543992
{txt}zero_privatize {c |}{col 16}{res}{space 2}-.0108343{col 28}{space 2} .0448956{col 39}{space 1}   -0.24{col 48}{space 3}0.809{col 56}{space 4}-.0988684{col 69}{space 3} .0771998
{txt}{space 2}zero_corrupt {c |}{col 16}{res}{space 2} .2209302{col 28}{space 2} .0463686{col 39}{space 1}    4.76{col 48}{space 3}0.000{col 56}{space 4} .1300077{col 69}{space 3} .3118526
{txt}{space 2}zero_poverty {c |}{col 16}{res}{space 2} .1015567{col 28}{space 2} .0461412{col 39}{space 1}    2.20{col 48}{space 3}0.028{col 56}{space 4} .0110802{col 69}{space 3} .1920332
{txt}{space 2}zero_climate {c |}{col 16}{res}{space 2} .0505237{col 28}{space 2} .0456419{col 39}{space 1}    1.11{col 48}{space 3}0.268{col 56}{space 4}-.0389737{col 69}{space 3} .1400211
{txt}zero_genderequ {c |}{col 16}{res}{space 2}  .105819{col 28}{space 2} .0456416{col 39}{space 1}    2.32{col 48}{space 3}0.020{col 56}{space 4} .0163222{col 69}{space 3} .1953158
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 2.943428{col 28}{space 2}  .068905{col 39}{space 1}   42.72{col 48}{space 3}0.000{col 56}{space 4} 2.808315{col 69}{space 3} 3.078541
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}    qcountry{col 14}{c |}{space 1}        3{col 27}{space 1}        0{col 39}{result}{space 1}        3{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
{res}{txt}
{com}. eststo taxes_amce
{txt}
{com}. 
. esttab support_amce cuts_amce taxes_amce using BH1.rtf, star(* 0.03 ** 0.005) b(4) r2 p mlabels(,titles) l addnote("** p<0.005; FDR=0.01; * p<0.03; FDR=0.05")
{res}{txt}(output written to {browse  `"BH1.rtf"'})

{com}. 
. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/mirkoheinzel/Documents/Publications/IMF/IMF_survey/1_replication/Heinzel_Metinosy_Kern_Reinsberg_ISQ24/Heinzel_Metinosy_Kern_Reinsberg_ISQ24_log.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 3 Dec 2024, 11:39:34
{txt}{.-}
{smcl}
{txt}{sf}{ul off}